A receding horizon Hoo control algorithm is presented for linear discrete time-delay system in the presence of constrained input and disturbances. Disturbance attenuation level is optimized at each time instant, and t...A receding horizon Hoo control algorithm is presented for linear discrete time-delay system in the presence of constrained input and disturbances. Disturbance attenuation level is optimized at each time instant, and the receding optimization problem includes several linear matrix inequality constraints. When the convex hull is applied to denote the saturating input, the algorithm has better performance. The numerical example can verify this result.展开更多
Receding horizon H∞ control scheme which can deal with both the H∞ disturbance attenuation and mean square stability is proposed for a class of discrete-time Markovian jump linear systems when minimizing a given qua...Receding horizon H∞ control scheme which can deal with both the H∞ disturbance attenuation and mean square stability is proposed for a class of discrete-time Markovian jump linear systems when minimizing a given quadratic performance criteria. First, a control law is established for jump systems based on pontryagin’s minimum principle and it can be constructed through numerical solution of iterative equations. The aim of this control strategy is to obtain an optimal control which can minimize the cost function under the worst disturbance at every sampling time. Due to the difficulty of the assurance of stability, then the above mentioned approach is improved by determining terminal weighting matrix which satisfies cost monotonicity condition. The control move which is calculated by using this type of terminal weighting matrix as boundary condition naturally guarantees the mean square stability of the closed-loop system. A sufficient condition for the existence of the terminal weighting matrix is presented in linear matrix inequality （LMI） form which can be solved efficiently by available software toolbox. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.展开更多
For a class of discrete-time singular stochastic systems with multi-state delay,the stabilization problem of receding horizon control(RHC)is concerned.Due to the difficulty in solving the proposed optimization problem...For a class of discrete-time singular stochastic systems with multi-state delay,the stabilization problem of receding horizon control(RHC)is concerned.Due to the difficulty in solving the proposed optimization problem,the RHC stabilization for such systems has not been solved.By adopting the forward and backward equation technique,the optimization problem is solved completely.A sufficient and necessary condition for the optimization controller to have a unique solution is given when the regularization and pulse-free conditions are satisfied.Based on this controller,an RHC stabilization condition is derived,which is in the form of linear matrix inequality.It is proved that the singular stochastic system with multi-state delay is stable in the mean-square sense under appropriate assumptions when the terminal weighting matrix satisfies the given inequality.Numerical examples show that the proposed RHC method is effective in stabilizing singular stochastic systems with multi-state delay.展开更多
The paper presents a new three-dimensional (3D) cooperative guidance approach by the receding horizon control (RHC) technique. The objective is to coordinate the impact time of a group of interceptor missiles against ...The paper presents a new three-dimensional (3D) cooperative guidance approach by the receding horizon control (RHC) technique. The objective is to coordinate the impact time of a group of interceptor missiles against the stationary target. The framework of a distributed RHC scheme is developed, in which each interceptor missile is assigned its own finite-horizon optimal control problem (FHOCP) and only shares the information with its neighbors. The solution of the local FHOCP is obtained by the constrained particle swarm optimization (PSO) method that is integrated into the distributed RHC framework with enhanced equality and inequality constraints. The numerical simulations show that the proposed guidance approach is feasible to implement the cooperative engagement with satisfied accuracy of target capture. Finally, the computation efficiency of the distributed RHC scheme is discussed in consideration of the PSO parameters, control update period and prediction horizon. (C) 2016 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.展开更多
Multiple unmanned air vehicles(UAVs)/unmanned ground vehicles(UGVs) heterogeneous cooperation provides a new breakthrough for the effective application of UAV and UGV.On the basis of introduction of UAV/UGV mathematic...Multiple unmanned air vehicles(UAVs)/unmanned ground vehicles(UGVs) heterogeneous cooperation provides a new breakthrough for the effective application of UAV and UGV.On the basis of introduction of UAV/UGV mathematical model,the characteristics of heterogeneous flocking is analyzed in detail.Two key issues are considered in multi-UGV subgroups,which are Reynolds Rule and Virtual Leader(VL).Receding Horizon Control(RHC) with Particle Swarm Optimization(PSO) is proposed for multiple UGVs flocking,and velocity vector control approach is adopted for multiple UAVs flocking.Then,multiple UAVs and UGVs heterogeneous tracking can be achieved by these two approaches.The feasibility and effectiveness of our proposed method are verified by comparative experiments with artificial potential field method.展开更多
To solve the receding horizon control （RHC） problem in an online manner, a novel numerical method called the indirect Radau pseudospectral method （IRPM） is proposed in this paper. Based on calculus of variations a...To solve the receding horizon control （RHC） problem in an online manner, a novel numerical method called the indirect Radau pseudospectral method （IRPM） is proposed in this paper. Based on calculus of variations and the first-order necessary optimality condition, the RHC problem for linear time-varying （LTV） system is transformed into the two-point boundary value problem （TPBVP）. The Radau pseudospectral approximation is employed to discretize the TPBVP into well-posed linear algebraic equations. The resulting linear algebraic equations are solved via a matrix partitioning approach afterwards to obtain the optimal feedback control law. For the nonlinear system, the linearization method or the quasi linearization method is employed to approximate the RHC problem with successive linear approximations. Subsequently, each linear problem is solved via the similar method which is used to solve the RHC problem for LTV system. Simulation results of three examples show that the IRPM is of high accuracy and of high compu- tation efficiency to solve the RHC problem and the stability of closed-loop systems is guaranteed.展开更多
This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle （UCAV） performing autonomous air-to-surface （A/S） attack. It combines the benefits...This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle （UCAV） performing autonomous air-to-surface （A/S） attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem （RHC-OCP）. In particular, an approximate elliptic launch acceptable region （LAR） model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom （2-DOF） receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.展开更多
This paper investigates the scheduling strategy of schedulable load in home energy management system(HEMS)under uncertain environment by proposing a distributionally robust optimization(DRO)method based on receding ho...This paper investigates the scheduling strategy of schedulable load in home energy management system(HEMS)under uncertain environment by proposing a distributionally robust optimization(DRO)method based on receding horizon optimization(RHO-DRO).First,the optimization model of HEMS,which contains uncertain variable outdoor temperature and hot water demand,is established and the scheduling problem is developed into a mixed integer linear programming(MILP)by using the DRO method based on the ambiguity sets of the probability distribution of uncertain variables.Combined with RHO,the MILP is solved in a rolling fashion using the latest update data related to uncertain variables.The simulation results demonstrate that the scheduling results are robust under uncertain environment while satisfying all operating constraints with little violation of user thermal comfort.Furthermore,compared with the robust optimization(RO)method,the RHO-DRO method proposed in this paper has a lower conservation and can save more electricity for users.展开更多
This paper mainly studies the problem of using UAVs to provide accurate remote target indication for hypersonic projectiles.Based on the optimal trajectory trends and feedback guidance methods,a new cooperative contro...This paper mainly studies the problem of using UAVs to provide accurate remote target indication for hypersonic projectiles.Based on the optimal trajectory trends and feedback guidance methods,a new cooperative control algorithm is proposed to optimize trajectories of multi-UAVs for target tracking in approaching stage.Based on UAV kinematics and sensor performance models,optimal trajectory trends of UAVs are analyzed theoretically.Then,feedback guidance methods are proposed under the optimal observation trends of UAVs in the approaching target stage,producing trajectories with far less computational complexity and performance very close to the best-known trajectories.Next,the sufficient condition for the UAV to form the optimal observation configuration by the feedback guidance method is presented,which guarantees that the proposed method can optimize the observation trajectory of the UAV in approaching stage.Finally,the feedback guidance method is numerically simulated.Simulation results demonstrate that the estimation performance of the feedback guidance method is superior to the Lyapunov guidance vector field(LGVF)method and verify the effectiveness of the proposed method.Additionally,compared with the receding horizon optimization(RHO)method,the proposed method has the same optimization ability as the RHO method and better real-time performance.展开更多
The on line computational burden related to model predictive control (MPC) of large scale constrained systems hampers its real time applications and limits it to slow dynamic process with moderate number of inputs....The on line computational burden related to model predictive control (MPC) of large scale constrained systems hampers its real time applications and limits it to slow dynamic process with moderate number of inputs. To avoid this, an efficient and fast algorithm based on aggregation optimization is proposed in this paper. It only optimizes the current control action at time instant k , while other future control sequences in the optimization horizon are approximated off line by the linear feedback control sequence, so the on line optimization can be converted into a low dimensional quadratic programming problem. Input constraints can be well handled in this scheme. The comparable performance is achieved with existing standard model predictive control algorithm. Simulation results well demonstrate its effectiveness.展开更多
The receding horizon control（RHC） problem is considered for nonlinear Markov jump systems which can be represented by Takagi-Sugeno fuzzy models subject to constraints both on control inputs and on observe outputs.I...The receding horizon control（RHC） problem is considered for nonlinear Markov jump systems which can be represented by Takagi-Sugeno fuzzy models subject to constraints both on control inputs and on observe outputs.In the given receding horizon,for each mode sequence of the T-S modeled nonlinear system with Markov jump parameter,the cost function is optimized by constraints on state trajectories,so that the optimization control input sequences are obtained in order to make the state into a terminal invariant set.Out of the receding horizon,the stability is guaranteed by searching a state feedback control law.Based on such stability analysis,a linear matrix inequality approach for designing receding horizon predictive controller for nonlinear systems subject to constraints both on the inputs and on the outputs is developed.The simulation shows the validity of this method.展开更多
An efficient algorithm is proposed for computing the solution to the constrained finite time optimal control （CFTOC） problem for discrete-time piecewise affine （PWA） systems with a quadratic performance index. The...An efficient algorithm is proposed for computing the solution to the constrained finite time optimal control （CFTOC） problem for discrete-time piecewise affine （PWA） systems with a quadratic performance index. The maximal positively invariant terminal set, which is feasible and invariant with respect to a feedback control law, is computed as terminal target set and an associated Lyapunov function is chosen as terminal cost. The combination of these two components guarantees constraint satisfaction and closed-loop stability for all time. The proposed algorithm combines a dynamic programming strategy with a multi-parametric quadratic programming solver and basic polyhedral manipulation. A numerical example shows that a larger stabilizable set of states can be obtained by the proposed algorithm than precious work.展开更多
This paper investigates the feedback control of hidden Markov process（HMP） in the face of loss of some observation processes.The control action facilitates or impedes some particular transitions from an inferred cur...This paper investigates the feedback control of hidden Markov process（HMP） in the face of loss of some observation processes.The control action facilitates or impedes some particular transitions from an inferred current state in the attempt to maximize the probability that the HMP is driven to a desirable absorbing state.This control problem is motivated by the need for judicious resource allocation to win an air operation involving two opposing forces.The effectiveness of a receding horizon control scheme based on the inferred discrete state is examined.Tolerance to loss of sensors that help determine the state of the air operation is achieved through a decentralized scheme that estimates a continuous state from measurements of linear models with additive noise.The discrete state of the HMP is identified using three well-known detection schemes.The sub-optimal control policy based on the detected state is implemented on-line in a closed-loop,where the air operation is simulated as a stochastic process with SimEvents,and the measurement process is simulated for a range of single sensor loss rates.展开更多
This paper considers the problems of formation and obstacle avoidance for multiagent systems.The objective is to design a term of agents that can reach a desired formation while avoiding collision with obstacles.To re...This paper considers the problems of formation and obstacle avoidance for multiagent systems.The objective is to design a term of agents that can reach a desired formation while avoiding collision with obstacles.To reduce the amount of information interaction between agents and target,we adopt the leader-follower formation strategy.By using the receding horizon control (RHC),an optimal problem is formulated in terms of cost minimization under constraints.Information on obstacles is incorporated online as sensed in a limited sensing range.The communication requirements between agents are that the followers should obtain the previous optimal control trajectory of the leader to each update time.The stability is guaranteed by adding a terminal-state penalty to the cost function and a terminal-state region to optimal problem.Finally,simulation studies are provided to verify the effectiveness of the proposed approach.展开更多
This paper considers the guidance and control problem of a flight vehicle with sidewindow detection. In order to guarantee the target remaining in the seeker＇s sight of view, the line of sight and the attitude of the...This paper considers the guidance and control problem of a flight vehicle with sidewindow detection. In order to guarantee the target remaining in the seeker＇s sight of view, the line of sight and the attitude of the flight vehicle should be under some constraints caused by the sidewindow, which leads to coupling between the guidance and the attitude dynamics model. To deal with the side-window constraints and the coupling, a novel Integrated Guidance and Control（IGC）design approach is proposed. Firstly, the relative motion equations are derived in the body-Line of Sight（LOS） coordinate system. And the guidance and control problem of the flight vehicle is formulated into an IGC problem with state constraints. Then, based on the singular perturbation method, the IGC problem is decomposed into the control design of the quasi-steady-state subsystem and the boundary-layer subsystem which can be designed separately. Finally, the receding horizon control is applied to the control design for the two subsystems. Simulation results show the effectiveness of the proposed approach.展开更多
Many human-machine collaborative support scheduling systems are used to aid human decision making by providing several optimal scheduling algorithms that do not take operator's attention into consideration.However...Many human-machine collaborative support scheduling systems are used to aid human decision making by providing several optimal scheduling algorithms that do not take operator's attention into consideration.However, the current systems should take advantage of the operator's attention to obtain the optimal solution.In this paper, we innovatively propose a human-machine collaborative support scheduling system of intelligence information from multi-UAVs based on eye-tracker. Firstly, the target recognition algorithm is applied to the images from the multiple unmanned aerial vehicles(multi-UAVs) to recognize the targets in the images. Then,the support system utilizes the eye tracker to gain the eye-gaze points which are intended to obtain the focused targets in the images. Finally, the heuristic scheduling algorithms take both the attributes of targets and the operator's attention into consideration to obtain the sequence of the images. As the processing time of the images collected by the multi-UAVs is uncertain, however the upper bounds and lower bounds of the processing time are known before. So the processing time of the images is modeled by the interval processing time. The objective of the scheduling problem is to minimize mean weighted completion time. This paper proposes some new polynomial time heuristic scheduling algorithms which firstly schedule the images including the focused targets. We conduct the scheduling experiments under six different distributions. The results indicate that the proposed algorithm is not sensitive to the different distributions of the processing time and has a negligible computational time. The absolute error of the best performing heuristic solution is only about 1%. Then, we incorporate the best performing heuristic algorithm into the human-machine collaborative support systems to verify the performance of the system.展开更多
Safe and effective autonomous navigation in dynamic environments is challenging for four-wheel independently driven steered mobile robots(FWIDSMRs)due to the flexible allocation of multiple maneuver modes.To address t...Safe and effective autonomous navigation in dynamic environments is challenging for four-wheel independently driven steered mobile robots(FWIDSMRs)due to the flexible allocation of multiple maneuver modes.To address this problem,this study proposes a novel multiple mode-based navigation system,which can achieve efficient motion planning and accurate tracking control.To reduce the calculation burden and obtain a comprehensive optimized global path,a kinodynamic interior-exterior cell exploration planning method,which leverages the hybrid space of available modes with an incorporated exploration guiding algorithm,is designed.By utilizing the sampled subgoals and the constructed global path,local planning is then performed to avoid unexpected obstacles and potential collisions.With the desired profile curvature and preselected mode,a fuzzy adaptive receding horizon control is proposed such that the online updating of the predictive horizon is realized to enhance the trajectory-following precision.The tracking controller design is achieved using the quadratic programming(QP)technique,and the primal-dual neural network optimization technique is used to solve the QP problem.Experimental results on a real-time FWIDSMR validate that the proposed method shows superior features over some existing methods in terms of efficiency and accuracy.展开更多
In this paper, the problem of designing a controller for a highly coupled constrained nonlinear boiler- turbine system is addressed with a predictive controller. First, a nonlinear predictive control is implemented by...In this paper, the problem of designing a controller for a highly coupled constrained nonlinear boiler- turbine system is addressed with a predictive controller. First, a nonlinear predictive control is implemented by genetic algorithm. Second, to guarantee fast output stabilization, an H-infinity fuzzy state-feedback tracking control is applied with a designed switching principle. The success of such a control structure is based on taking advantage of the optimal input sequence derived from the nonlinear predictive control based on artificial intelligent while ensuring a fast decay of the steady state error. Simulation results of the proposed design are given to illustrate its effectiveness and compared to other control schemes.展开更多
This paper investigates a fundamental problem of stabilization for time-varying multiplicative noise stochastic systems. A necessary and sufficient stabilization condition is presented based on the receding horizon ap...This paper investigates a fundamental problem of stabilization for time-varying multiplicative noise stochastic systems. A necessary and sufficient stabilization condition is presented based on the receding horizon approach. The explicit time-varying controller is designed if the condition is satisfied. The presented results are new to the best of our knowledge.展开更多
The stabilization with receding horizon control （RHC） of It5 stochastic time-varying systems is studied in this paper. Based on monotonically non-increasing of optimal cost and stochastic Lyapunov stability theory, ...The stabilization with receding horizon control （RHC） of It5 stochastic time-varying systems is studied in this paper. Based on monotonically non-increasing of optimal cost and stochastic Lyapunov stability theory, a necessary and sufficient stabilization condition on the terminal weighting matrix is proposed, which guarantees the mean-square stability of the closed-loop system. The explicit receding horizon controller is obtained by employing stochastic maximum principle. Simulations demonstrate the effectiveness of the proposed method.展开更多
文摘A receding horizon Hoo control algorithm is presented for linear discrete time-delay system in the presence of constrained input and disturbances. Disturbance attenuation level is optimized at each time instant, and the receding optimization problem includes several linear matrix inequality constraints. When the convex hull is applied to denote the saturating input, the algorithm has better performance. The numerical example can verify this result.
基金supported by the National Natural Science Foundation of China (60974001)Jiangsu "Six Personnel Peak" Talent-Funded Projects
文摘Receding horizon H∞ control scheme which can deal with both the H∞ disturbance attenuation and mean square stability is proposed for a class of discrete-time Markovian jump linear systems when minimizing a given quadratic performance criteria. First, a control law is established for jump systems based on pontryagin’s minimum principle and it can be constructed through numerical solution of iterative equations. The aim of this control strategy is to obtain an optimal control which can minimize the cost function under the worst disturbance at every sampling time. Due to the difficulty of the assurance of stability, then the above mentioned approach is improved by determining terminal weighting matrix which satisfies cost monotonicity condition. The control move which is calculated by using this type of terminal weighting matrix as boundary condition naturally guarantees the mean square stability of the closed-loop system. A sufficient condition for the existence of the terminal weighting matrix is presented in linear matrix inequality （LMI） form which can be solved efficiently by available software toolbox. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.
基金the Natural Science Foundation of Shandong Province (No.ZR2020MF063)the National Natural Science Foundation of China (No.61873332)。
文摘For a class of discrete-time singular stochastic systems with multi-state delay,the stabilization problem of receding horizon control(RHC)is concerned.Due to the difficulty in solving the proposed optimization problem,the RHC stabilization for such systems has not been solved.By adopting the forward and backward equation technique,the optimization problem is solved completely.A sufficient and necessary condition for the optimization controller to have a unique solution is given when the regularization and pulse-free conditions are satisfied.Based on this controller,an RHC stabilization condition is derived,which is in the form of linear matrix inequality.It is proved that the singular stochastic system with multi-state delay is stable in the mean-square sense under appropriate assumptions when the terminal weighting matrix satisfies the given inequality.Numerical examples show that the proposed RHC method is effective in stabilizing singular stochastic systems with multi-state delay.
基金co-supported by the National Natural Science Foundation of China(Nos. 61273349 and 61573043)
文摘The paper presents a new three-dimensional (3D) cooperative guidance approach by the receding horizon control (RHC) technique. The objective is to coordinate the impact time of a group of interceptor missiles against the stationary target. The framework of a distributed RHC scheme is developed, in which each interceptor missile is assigned its own finite-horizon optimal control problem (FHOCP) and only shares the information with its neighbors. The solution of the local FHOCP is obtained by the constrained particle swarm optimization (PSO) method that is integrated into the distributed RHC framework with enhanced equality and inequality constraints. The numerical simulations show that the proposed guidance approach is feasible to implement the cooperative engagement with satisfied accuracy of target capture. Finally, the computation efficiency of the distributed RHC scheme is discussed in consideration of the PSO parameters, control update period and prediction horizon. (C) 2016 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.
基金supported by the National Natural Science Foundation of China (Grant Nos. 60975072 and 60604009)Aeronautical Science Foundation of China (Grant No. 2008ZC01006)+4 种基金Program for New Century Excellent Talents in University of China (Grant No. NCET-10-0021)the Fundamental Research Funds for the Central Universities of China (Grant No. YWF-10-01-A18)Beijing NOVA Program Foundation (Grant No. 2007A017)open Fund of the State Key Laboratory of Virtual Reality Technology and SystemsOpen Fund of the Provincial Key Laboratory for Information Processing Technology, Suzhou University, China (Grant No. KJS1020)
文摘Multiple unmanned air vehicles(UAVs)/unmanned ground vehicles(UGVs) heterogeneous cooperation provides a new breakthrough for the effective application of UAV and UGV.On the basis of introduction of UAV/UGV mathematical model,the characteristics of heterogeneous flocking is analyzed in detail.Two key issues are considered in multi-UGV subgroups,which are Reynolds Rule and Virtual Leader(VL).Receding Horizon Control(RHC) with Particle Swarm Optimization(PSO) is proposed for multiple UGVs flocking,and velocity vector control approach is adopted for multiple UAVs flocking.Then,multiple UAVs and UGVs heterogeneous tracking can be achieved by these two approaches.The feasibility and effectiveness of our proposed method are verified by comparative experiments with artificial potential field method.
基金supported by the National Natural Science Foundation of China(Nos.61174221 and 61402039)
文摘To solve the receding horizon control （RHC） problem in an online manner, a novel numerical method called the indirect Radau pseudospectral method （IRPM） is proposed in this paper. Based on calculus of variations and the first-order necessary optimality condition, the RHC problem for linear time-varying （LTV） system is transformed into the two-point boundary value problem （TPBVP）. The Radau pseudospectral approximation is employed to discretize the TPBVP into well-posed linear algebraic equations. The resulting linear algebraic equations are solved via a matrix partitioning approach afterwards to obtain the optimal feedback control law. For the nonlinear system, the linearization method or the quasi linearization method is employed to approximate the RHC problem with successive linear approximations. Subsequently, each linear problem is solved via the similar method which is used to solve the RHC problem for LTV system. Simulation results of three examples show that the IRPM is of high accuracy and of high compu- tation efficiency to solve the RHC problem and the stability of closed-loop systems is guaranteed.
基金supported by the National Defense Foundation of China(No.403060103)
文摘This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle （UCAV） performing autonomous air-to-surface （A/S） attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem （RHC-OCP）. In particular, an approximate elliptic launch acceptable region （LAR） model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom （2-DOF） receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.
基金supported by the National Key Research and Development Program of China(Grant No.2016YFB0901102).
文摘This paper investigates the scheduling strategy of schedulable load in home energy management system(HEMS)under uncertain environment by proposing a distributionally robust optimization(DRO)method based on receding horizon optimization(RHO-DRO).First,the optimization model of HEMS,which contains uncertain variable outdoor temperature and hot water demand,is established and the scheduling problem is developed into a mixed integer linear programming(MILP)by using the DRO method based on the ambiguity sets of the probability distribution of uncertain variables.Combined with RHO,the MILP is solved in a rolling fashion using the latest update data related to uncertain variables.The simulation results demonstrate that the scheduling results are robust under uncertain environment while satisfying all operating constraints with little violation of user thermal comfort.Furthermore,compared with the robust optimization(RO)method,the RHO-DRO method proposed in this paper has a lower conservation and can save more electricity for users.
基金support from the National Natural Science Foundation of China(No.61773395)。
文摘This paper mainly studies the problem of using UAVs to provide accurate remote target indication for hypersonic projectiles.Based on the optimal trajectory trends and feedback guidance methods,a new cooperative control algorithm is proposed to optimize trajectories of multi-UAVs for target tracking in approaching stage.Based on UAV kinematics and sensor performance models,optimal trajectory trends of UAVs are analyzed theoretically.Then,feedback guidance methods are proposed under the optimal observation trends of UAVs in the approaching target stage,producing trajectories with far less computational complexity and performance very close to the best-known trajectories.Next,the sufficient condition for the UAV to form the optimal observation configuration by the feedback guidance method is presented,which guarantees that the proposed method can optimize the observation trajectory of the UAV in approaching stage.Finally,the feedback guidance method is numerically simulated.Simulation results demonstrate that the estimation performance of the feedback guidance method is superior to the Lyapunov guidance vector field(LGVF)method and verify the effectiveness of the proposed method.Additionally,compared with the receding horizon optimization(RHO)method,the proposed method has the same optimization ability as the RHO method and better real-time performance.
文摘The on line computational burden related to model predictive control (MPC) of large scale constrained systems hampers its real time applications and limits it to slow dynamic process with moderate number of inputs. To avoid this, an efficient and fast algorithm based on aggregation optimization is proposed in this paper. It only optimizes the current control action at time instant k , while other future control sequences in the optimization horizon are approximated off line by the linear feedback control sequence, so the on line optimization can be converted into a low dimensional quadratic programming problem. Input constraints can be well handled in this scheme. The comparable performance is achieved with existing standard model predictive control algorithm. Simulation results well demonstrate its effectiveness.
基金supported by the National Natural Science Foundation of China (6097400160904045)+1 种基金National Natural Science Foundation of Jiangsu Province (BK2009068)Six Projects Sponsoring Talent Summits of Jiangsu Province
文摘The receding horizon control（RHC） problem is considered for nonlinear Markov jump systems which can be represented by Takagi-Sugeno fuzzy models subject to constraints both on control inputs and on observe outputs.In the given receding horizon,for each mode sequence of the T-S modeled nonlinear system with Markov jump parameter,the cost function is optimized by constraints on state trajectories,so that the optimization control input sequences are obtained in order to make the state into a terminal invariant set.Out of the receding horizon,the stability is guaranteed by searching a state feedback control law.Based on such stability analysis,a linear matrix inequality approach for designing receding horizon predictive controller for nonlinear systems subject to constraints both on the inputs and on the outputs is developed.The simulation shows the validity of this method.
基金supported by the National Natural Science Foundation of China (60702033)Natural Science Foundation of Zhe-jiang Province (Y107440)
文摘An efficient algorithm is proposed for computing the solution to the constrained finite time optimal control （CFTOC） problem for discrete-time piecewise affine （PWA） systems with a quadratic performance index. The maximal positively invariant terminal set, which is feasible and invariant with respect to a feedback control law, is computed as terminal target set and an associated Lyapunov function is chosen as terminal cost. The combination of these two components guarantees constraint satisfaction and closed-loop stability for all time. The proposed algorithm combines a dynamic programming strategy with a multi-parametric quadratic programming solver and basic polyhedral manipulation. A numerical example shows that a larger stabilizable set of states can be obtained by the proposed algorithm than precious work.
文摘This paper investigates the feedback control of hidden Markov process（HMP） in the face of loss of some observation processes.The control action facilitates or impedes some particular transitions from an inferred current state in the attempt to maximize the probability that the HMP is driven to a desirable absorbing state.This control problem is motivated by the need for judicious resource allocation to win an air operation involving two opposing forces.The effectiveness of a receding horizon control scheme based on the inferred discrete state is examined.Tolerance to loss of sensors that help determine the state of the air operation is achieved through a decentralized scheme that estimates a continuous state from measurements of linear models with additive noise.The discrete state of the HMP is identified using three well-known detection schemes.The sub-optimal control policy based on the detected state is implemented on-line in a closed-loop,where the air operation is simulated as a stochastic process with SimEvents,and the measurement process is simulated for a range of single sensor loss rates.
基金supported by the National Basic Research Program of China (973 Program) (No. 2010CB731800)the Key Program of National Natural Science Foundation of China (No. 60934003),the National Natural Science Foundation of China (No. 61074065,60974018)+1 种基金the Key Project for Natural Science Research of Hebei Education Department (No. ZD200908)Key Project for Shanghai Committee of Science and Technology(No. 08511501600)
文摘This paper considers the problems of formation and obstacle avoidance for multiagent systems.The objective is to design a term of agents that can reach a desired formation while avoiding collision with obstacles.To reduce the amount of information interaction between agents and target,we adopt the leader-follower formation strategy.By using the receding horizon control (RHC),an optimal problem is formulated in terms of cost minimization under constraints.Information on obstacles is incorporated online as sensed in a limited sensing range.The communication requirements between agents are that the followers should obtain the previous optimal control trajectory of the leader to each update time.The stability is guaranteed by adding a terminal-state penalty to the cost function and a terminal-state region to optimal problem.Finally,simulation studies are provided to verify the effectiveness of the proposed approach.
基金supported by National Natural Science Foundation of China (Nos. 61473099 and 61333001)
文摘This paper considers the guidance and control problem of a flight vehicle with sidewindow detection. In order to guarantee the target remaining in the seeker＇s sight of view, the line of sight and the attitude of the flight vehicle should be under some constraints caused by the sidewindow, which leads to coupling between the guidance and the attitude dynamics model. To deal with the side-window constraints and the coupling, a novel Integrated Guidance and Control（IGC）design approach is proposed. Firstly, the relative motion equations are derived in the body-Line of Sight（LOS） coordinate system. And the guidance and control problem of the flight vehicle is formulated into an IGC problem with state constraints. Then, based on the singular perturbation method, the IGC problem is decomposed into the control design of the quasi-steady-state subsystem and the boundary-layer subsystem which can be designed separately. Finally, the receding horizon control is applied to the control design for the two subsystems. Simulation results show the effectiveness of the proposed approach.
基金the National Natural Science Foundation of China(No.61403410)
文摘Many human-machine collaborative support scheduling systems are used to aid human decision making by providing several optimal scheduling algorithms that do not take operator's attention into consideration.However, the current systems should take advantage of the operator's attention to obtain the optimal solution.In this paper, we innovatively propose a human-machine collaborative support scheduling system of intelligence information from multi-UAVs based on eye-tracker. Firstly, the target recognition algorithm is applied to the images from the multiple unmanned aerial vehicles(multi-UAVs) to recognize the targets in the images. Then,the support system utilizes the eye tracker to gain the eye-gaze points which are intended to obtain the focused targets in the images. Finally, the heuristic scheduling algorithms take both the attributes of targets and the operator's attention into consideration to obtain the sequence of the images. As the processing time of the images collected by the multi-UAVs is uncertain, however the upper bounds and lower bounds of the processing time are known before. So the processing time of the images is modeled by the interval processing time. The objective of the scheduling problem is to minimize mean weighted completion time. This paper proposes some new polynomial time heuristic scheduling algorithms which firstly schedule the images including the focused targets. We conduct the scheduling experiments under six different distributions. The results indicate that the proposed algorithm is not sensitive to the different distributions of the processing time and has a negligible computational time. The absolute error of the best performing heuristic solution is only about 1%. Then, we incorporate the best performing heuristic algorithm into the human-machine collaborative support systems to verify the performance of the system.
基金The work was funded in part by the Guangdong Major Science and Technology Project,China(Grant Nos.2019B090919003 and 2017B090913001)in part by the China Postdoctoral Science Foundation(Grant No.2019M650179)+2 种基金in part by the Guangdong Innovative and Entrepreneurial Research Team Program,China(Grant No.2019ZT08Z780)in part by the Dongguan Innovative Research Team Program,China(Grant No.201536000100031)in part by the Guangdong HUST Industrial Technology Research Institute,Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization,China(Grant No.2020B1212060014).
文摘Safe and effective autonomous navigation in dynamic environments is challenging for four-wheel independently driven steered mobile robots(FWIDSMRs)due to the flexible allocation of multiple maneuver modes.To address this problem,this study proposes a novel multiple mode-based navigation system,which can achieve efficient motion planning and accurate tracking control.To reduce the calculation burden and obtain a comprehensive optimized global path,a kinodynamic interior-exterior cell exploration planning method,which leverages the hybrid space of available modes with an incorporated exploration guiding algorithm,is designed.By utilizing the sampled subgoals and the constructed global path,local planning is then performed to avoid unexpected obstacles and potential collisions.With the desired profile curvature and preselected mode,a fuzzy adaptive receding horizon control is proposed such that the online updating of the predictive horizon is realized to enhance the trajectory-following precision.The tracking controller design is achieved using the quadratic programming(QP)technique,and the primal-dual neural network optimization technique is used to solve the QP problem.Experimental results on a real-time FWIDSMR validate that the proposed method shows superior features over some existing methods in terms of efficiency and accuracy.
基金supported by the Chinese Scholarship Council, the Project of Chinese Ministry of Education (No. 108060)the Doctoral Fund of Ministry of Education of China (No. 20090092110051)the National Natural Science Foundation of China (Nos. 51036002, 51076027)
文摘In this paper, the problem of designing a controller for a highly coupled constrained nonlinear boiler- turbine system is addressed with a predictive controller. First, a nonlinear predictive control is implemented by genetic algorithm. Second, to guarantee fast output stabilization, an H-infinity fuzzy state-feedback tracking control is applied with a designed switching principle. The success of such a control structure is based on taking advantage of the optimal input sequence derived from the nonlinear predictive control based on artificial intelligent while ensuring a fast decay of the steady state error. Simulation results of the proposed design are given to illustrate its effectiveness and compared to other control schemes.
基金This work was supported by the Taishan Scholar Construction Engineering by Shandong Government and the National Natural Science Foundation of China （Nos. 61120106011, 61203029）.
文摘This paper investigates a fundamental problem of stabilization for time-varying multiplicative noise stochastic systems. A necessary and sufficient stabilization condition is presented based on the receding horizon approach. The explicit time-varying controller is designed if the condition is satisfied. The presented results are new to the best of our knowledge.
基金supported by the Taishan Scholar Construction Engineering by Shandong Governmentthe National Natural Science Foundation of China under Grant Nos.61120106011 and 61573221
文摘The stabilization with receding horizon control （RHC） of It5 stochastic time-varying systems is studied in this paper. Based on monotonically non-increasing of optimal cost and stochastic Lyapunov stability theory, a necessary and sufficient stabilization condition on the terminal weighting matrix is proposed, which guarantees the mean-square stability of the closed-loop system. The explicit receding horizon controller is obtained by employing stochastic maximum principle. Simulations demonstrate the effectiveness of the proposed method.
