Multibody system dynamics provides a strong tool for the estimation of dynamic performances and the optimization of multisystem robot design. It can be described with differential algebraic equations(DAEs). In this pa...Multibody system dynamics provides a strong tool for the estimation of dynamic performances and the optimization of multisystem robot design. It can be described with differential algebraic equations(DAEs). In this paper, a particle swarm optimization(PSO) method is introduced to solve and control a symplectic multibody system for the first time. It is first combined with the symplectic method to solve problems in uncontrolled and controlled robotic arm systems. It is shown that the results conserve the energy and keep the constraints of the chaotic motion, which demonstrates the efficiency, accuracy, and time-saving ability of the method. To make the system move along the pre-planned path, which is a functional extremum problem, a double-PSO-based instantaneous optimal control is introduced. Examples are performed to test the effectiveness of the double-PSO-based instantaneous optimal control. The results show that the method has high accuracy, a fast convergence speed, and a wide range of applications.All the above verify the immense potential applications of the PSO method in multibody system dynamics.展开更多
Based on the concept of optimal control solution to dynamic system parameters identification and the optimal control theory of deterministic system,dyna-mics system parameters identfication problem is brought into cor...Based on the concept of optimal control solution to dynamic system parameters identification and the optimal control theory of deterministic system,dyna-mics system parameters identfication problem is brought into correspondence with optimal control problem. Then the theory and algorithm of optimal control are introduced into the study of dynamic system parameters identification. According to the theory of Hamilton-Jacobi-Bellman (HJB) equations solution, the existence and uniqueness of optimal control solution to dynamic system parameters identification are resolved in this paper. At last, the parameters identification algorithm of determi-nistic dynamic system is presented also based on above mentioned theory and concept.展开更多
Based on the contents Of part (Ⅰ) and stochastic optimal control theory, the concept of optimal control solution to parameters identification of stochastic dynamic system is discussed at first. For the completeness o...Based on the contents Of part (Ⅰ) and stochastic optimal control theory, the concept of optimal control solution to parameters identification of stochastic dynamic system is discussed at first. For the completeness of the theory developed in this paper and part (Ⅰ), then the procedure of establishing HamiltonJacobi-Bellman (HJB) equations of parameters identification problem is presented.And then, parameters identification algorithm of stochastic dynamic system is introduced. At last, an application example-local nonlinear parameters identification of dynamic system is presented.展开更多
Loss of Control (LOC) is the primary factor responsible for the majority of fatal air accidents during past decade. LOC is characterized by the pilot’s inability to control the aircraft and is typically associated wi...Loss of Control (LOC) is the primary factor responsible for the majority of fatal air accidents during past decade. LOC is characterized by the pilot’s inability to control the aircraft and is typically associated with unpredictable behavior, potentially leading to loss of the aircraft and life. In this work, the minimum time dynamic optimization problem to LOC is treated using Pontryagin’s Maximum Principle (PMP). The resulting two point boundary value problem is solved using stochastic shooting point methods via a differential evolution scheme (DE). The minimum time until LOC metric is computed for corresponding spatial control limits. Simulations are performed using a linearized longitudinal aircraft model to illustrate the concept.展开更多
Methods based on numerical optimization are useful and effective in the design of control systems. This paper describes the design of retarded fractional delay differential systems （RFDDSs） by the method of inequali...Methods based on numerical optimization are useful and effective in the design of control systems. This paper describes the design of retarded fractional delay differential systems （RFDDSs） by the method of inequalities, in which the design problem is formulated so that it is suitable for solution by numerical methods. Zakian＇s original formulation, which was first proposed in connection with rational systems, is extended to the case of RFDDSs. In making the use of this formulation possible for RFDDSs, the associated stability problems are resolved by using the stability test and the numerical algorithm for computing the abscissa of stability recently developed by the authors. During the design process, the time responses are obtained by a known method for the numerical inversion of Laplace transforms. Two numerical examples are given, where fractional controllers are designed for a time-delay and a heat-conduction plants.展开更多
A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical an...A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.展开更多
A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rat...A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.展开更多
The newly proposed mega sub-controlled structure system(MSCSS)and related studies have drawn the attention of civil engineers for practice in improving the performance and enhancing the structural effectiveness of meg...The newly proposed mega sub-controlled structure system(MSCSS)and related studies have drawn the attention of civil engineers for practice in improving the performance and enhancing the structural effectiveness of mega frame structures.However,there is still a need for improvement to its basic structural arrangement.In this project,an advanced,reasonable arrangement of mega sub-controlled structure models,composed of three mega stories with different numbers and arrangements of substructures,are designed to investigate the control performance of the models and obtain the optimal model configuration(model with minimum acceleration and displacement responses)under strong earthquake excitation.In addition,the dynamic parameters that affect the performance effectiveness of the optimal model of MSCSS are studied and discussed.The area of the relative stiffness ratio RD,with different mass ratio MR,within which the acceleration and displacement of the optimal model of MSCSS reaches its optimum(minimum)value is considered as an optimum region.It serves as a useful tool in practical engineering design.The study demonstrates that the proposed MSCSS configuration can efficiently control the displacement and acceleration of high rise buildings.In addition,some analytical guidelines are provided for selecting the control parameters of the structure.展开更多
This paper considers dealing with path constraints in the framework of the improved control vector iteration （CVI） approach. Two available ways for enforcing equality path constraints are presented, which can be dir...This paper considers dealing with path constraints in the framework of the improved control vector iteration （CVI） approach. Two available ways for enforcing equality path constraints are presented, which can be directly incorporated into the improved CVI approach. Inequality path constraints are much more difficult to deal with, even for small scale problems, because the time intervals where the inequality path constraints are active are unknown in advance. To overcome the challenge, the ll penalty function and a novel smoothing technique are in-troduced, leading to a new effective approach. Moreover, on the basis of the relevant theorems, a numerical algo-rithm is proposed for nonlinear dynamic optimization problems with inequality path constraints. Results obtained from the classic batch reaCtor operation problem are in agreement with the literature reoorts, and the comoutational efficiency is also high.展开更多
Joints are widely used in many kinds of engineering structures, which often leads to the structures to exhibit local nonlinearities, and moreover, they are difficult to model because the complexity of configuration an...Joints are widely used in many kinds of engineering structures, which often leads to the structures to exhibit local nonlinearities, and moreover, they are difficult to model because the complexity of configuration and operating mode. Therefore, parameter identification technique is usually used to model the joints and estimate the model parameters. A novel parameter identification method of nonlinear joints inside a structure is introduced in this paper, by expressing the force transmitted by the joint as a function of its mechanical state and assuming that the other part of the structure is known. In general, the force transmitted by the joints inside a structure and their mechanical state are difficult to measure. To overcome this difficulty, the algorithm of stochastic optimal control is used to identify the force transmitted by the joints and their mechanical state. After that, parameters of the joints can be identified by least squares parameter estimation method. Numerical simulation examples are also given to validate the effectiveness of the proposed method.展开更多
The TOMS zonal average total ozone data in the Northern Hemisphere are decomposed with the empirical orthogonal function (EOF) method. According to the features of the spatial characteristic vectors, the characteristi...The TOMS zonal average total ozone data in the Northern Hemisphere are decomposed with the empirical orthogonal function (EOF) method. According to the features of the spatial characteristic vectors, the characteristic vectors that have been obtained with EOF method can be used as the ordered orthogonal radixes to unfold the phase space. After the corresponding time functions are embedded in phase space, the traces of the state vectors of the regional ozonosphere dynamical system are constructed, and can be used to describe the attractor integral information of the asymptotic state of the regional ozonosphere system and the dynamical features of the regional ozonosphere system, and then the embedded saturation dimension of the regional ozonosphere system attractor is successfully obtained. Based on these works mentioned above, by using the time function series we solve a problem contrary to the numerical solution and retrieve the control parameters of the state equations in which quadratic nonlinear terms are included, and then the dynamical models that can objectively reflect the temporal variation of the regional ozonosphere system are finally established.展开更多
Many industrial processes such as heating furnaces have over damping dynamic characteristics. Based on an innovative impulse response model, a method of identification and control for the over damping plant is introdu...Many industrial processes such as heating furnaces have over damping dynamic characteristics. Based on an innovative impulse response model, a method of identification and control for the over damping plant is introduced in the paper. The number of parameters of the model is much less than conventional impulse response model. The model based on tuning procedure of numerical optimum PID controller parameters is presented. For an actual instance, a large scale airflow circulatory resistance furnace control system with cascades of time delays is developed. In the system, the optimum PID control is used in the inner loop. A nonlinear PI compensation control is applied in the outer loop. The coordinating control among each output is realized by a fuzzy control strategy. A process surveillance organization monitors running situation of system and tunes controller parameters.展开更多
A strategy is proposed based on the stochastic averaging method for quasi non- integrable Hamiltonian systems and the stochastic dynamical programming principle.The pro- posed strategy can be used to design nonlinear ...A strategy is proposed based on the stochastic averaging method for quasi non- integrable Hamiltonian systems and the stochastic dynamical programming principle.The pro- posed strategy can be used to design nonlinear stochastic optimal control to minimize the response of quasi non-integrable Hamiltonian systems subject to Gaussian white noise excitation.By using the stochastic averaging method for quasi non-integrable Hamiltonian systems the equations of motion of a controlled quasi non-integrable Hamiltonian system is reduced to a one-dimensional av- eraged It stochastic differential equation.By using the stochastic dynamical programming princi- ple the dynamical programming equation for minimizing the response of the system is formulated. The optimal control law is derived from the dynamical programming equation and the bounded control constraints.The response of optimally controlled systems is predicted through solving the FPK equation associated with It stochastic differential equation.An example is worked out in detail to illustrate the application of the control strategy proposed.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.91648101 and11672233)the Northwestern Polytechnical University(NPU)Foundation for Fundamental Research(No.3102017AX008)the National Training Program of Innovation and Entrepreneurship for Undergraduates(No.S201710699033)
文摘Multibody system dynamics provides a strong tool for the estimation of dynamic performances and the optimization of multisystem robot design. It can be described with differential algebraic equations(DAEs). In this paper, a particle swarm optimization(PSO) method is introduced to solve and control a symplectic multibody system for the first time. It is first combined with the symplectic method to solve problems in uncontrolled and controlled robotic arm systems. It is shown that the results conserve the energy and keep the constraints of the chaotic motion, which demonstrates the efficiency, accuracy, and time-saving ability of the method. To make the system move along the pre-planned path, which is a functional extremum problem, a double-PSO-based instantaneous optimal control is introduced. Examples are performed to test the effectiveness of the double-PSO-based instantaneous optimal control. The results show that the method has high accuracy, a fast convergence speed, and a wide range of applications.All the above verify the immense potential applications of the PSO method in multibody system dynamics.
文摘Based on the concept of optimal control solution to dynamic system parameters identification and the optimal control theory of deterministic system,dyna-mics system parameters identfication problem is brought into correspondence with optimal control problem. Then the theory and algorithm of optimal control are introduced into the study of dynamic system parameters identification. According to the theory of Hamilton-Jacobi-Bellman (HJB) equations solution, the existence and uniqueness of optimal control solution to dynamic system parameters identification are resolved in this paper. At last, the parameters identification algorithm of determi-nistic dynamic system is presented also based on above mentioned theory and concept.
文摘Based on the contents Of part (Ⅰ) and stochastic optimal control theory, the concept of optimal control solution to parameters identification of stochastic dynamic system is discussed at first. For the completeness of the theory developed in this paper and part (Ⅰ), then the procedure of establishing HamiltonJacobi-Bellman (HJB) equations of parameters identification problem is presented.And then, parameters identification algorithm of stochastic dynamic system is introduced. At last, an application example-local nonlinear parameters identification of dynamic system is presented.
文摘Loss of Control (LOC) is the primary factor responsible for the majority of fatal air accidents during past decade. LOC is characterized by the pilot’s inability to control the aircraft and is typically associated with unpredictable behavior, potentially leading to loss of the aircraft and life. In this work, the minimum time dynamic optimization problem to LOC is treated using Pontryagin’s Maximum Principle (PMP). The resulting two point boundary value problem is solved using stochastic shooting point methods via a differential evolution scheme (DE). The minimum time until LOC metric is computed for corresponding spatial control limits. Simulations are performed using a linearized longitudinal aircraft model to illustrate the concept.
基金supported by the AUN/SEED-Net collaborative research program.
文摘Methods based on numerical optimization are useful and effective in the design of control systems. This paper describes the design of retarded fractional delay differential systems （RFDDSs） by the method of inequalities, in which the design problem is formulated so that it is suitable for solution by numerical methods. Zakian＇s original formulation, which was first proposed in connection with rational systems, is extended to the case of RFDDSs. In making the use of this formulation possible for RFDDSs, the associated stability problems are resolved by using the stability test and the numerical algorithm for computing the abscissa of stability recently developed by the authors. During the design process, the time responses are obtained by a known method for the numerical inversion of Laplace transforms. Two numerical examples are given, where fractional controllers are designed for a time-delay and a heat-conduction plants.
文摘A certain number of considerations should be taken into account in the dynamic control of robot manipulators as highly complex non-linear systems.In this article,we provide a detailed presentation of the mechanical and electrical impli- cations of robots equipped with DC motor actuators.This model takes into account all non-linear aspects of the system.Then,we develop computational algorithms for optimal control based on dynamic programming.The robot's trajectory must be predefined,but performance criteria and constraints applying to the system are not limited and we may adapt them freely to the robot and the task being studied.As an example,a manipulator arm with 3 degrees of freedom is analyzed.
基金Project(2013CB733605)supported by the National Basic Research Program of ChinaProject(21176073)supported by the National Natural Science Foundation of China
文摘A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.
基金National Natural Science Foundation of China under Grant No.51878274。
文摘The newly proposed mega sub-controlled structure system(MSCSS)and related studies have drawn the attention of civil engineers for practice in improving the performance and enhancing the structural effectiveness of mega frame structures.However,there is still a need for improvement to its basic structural arrangement.In this project,an advanced,reasonable arrangement of mega sub-controlled structure models,composed of three mega stories with different numbers and arrangements of substructures,are designed to investigate the control performance of the models and obtain the optimal model configuration(model with minimum acceleration and displacement responses)under strong earthquake excitation.In addition,the dynamic parameters that affect the performance effectiveness of the optimal model of MSCSS are studied and discussed.The area of the relative stiffness ratio RD,with different mass ratio MR,within which the acceleration and displacement of the optimal model of MSCSS reaches its optimum(minimum)value is considered as an optimum region.It serves as a useful tool in practical engineering design.The study demonstrates that the proposed MSCSS configuration can efficiently control the displacement and acceleration of high rise buildings.In addition,some analytical guidelines are provided for selecting the control parameters of the structure.
基金Supported by the National Natural Science Foundation of China(U1162130)the National High Technology Research and Development Program of China(2006AA05Z226)Outstanding Youth Science Foundation of Zhejiang Province(R4100133)
文摘This paper considers dealing with path constraints in the framework of the improved control vector iteration （CVI） approach. Two available ways for enforcing equality path constraints are presented, which can be directly incorporated into the improved CVI approach. Inequality path constraints are much more difficult to deal with, even for small scale problems, because the time intervals where the inequality path constraints are active are unknown in advance. To overcome the challenge, the ll penalty function and a novel smoothing technique are in-troduced, leading to a new effective approach. Moreover, on the basis of the relevant theorems, a numerical algo-rithm is proposed for nonlinear dynamic optimization problems with inequality path constraints. Results obtained from the classic batch reaCtor operation problem are in agreement with the literature reoorts, and the comoutational efficiency is also high.
文摘Joints are widely used in many kinds of engineering structures, which often leads to the structures to exhibit local nonlinearities, and moreover, they are difficult to model because the complexity of configuration and operating mode. Therefore, parameter identification technique is usually used to model the joints and estimate the model parameters. A novel parameter identification method of nonlinear joints inside a structure is introduced in this paper, by expressing the force transmitted by the joint as a function of its mechanical state and assuming that the other part of the structure is known. In general, the force transmitted by the joints inside a structure and their mechanical state are difficult to measure. To overcome this difficulty, the algorithm of stochastic optimal control is used to identify the force transmitted by the joints and their mechanical state. After that, parameters of the joints can be identified by least squares parameter estimation method. Numerical simulation examples are also given to validate the effectiveness of the proposed method.
文摘The TOMS zonal average total ozone data in the Northern Hemisphere are decomposed with the empirical orthogonal function (EOF) method. According to the features of the spatial characteristic vectors, the characteristic vectors that have been obtained with EOF method can be used as the ordered orthogonal radixes to unfold the phase space. After the corresponding time functions are embedded in phase space, the traces of the state vectors of the regional ozonosphere dynamical system are constructed, and can be used to describe the attractor integral information of the asymptotic state of the regional ozonosphere system and the dynamical features of the regional ozonosphere system, and then the embedded saturation dimension of the regional ozonosphere system attractor is successfully obtained. Based on these works mentioned above, by using the time function series we solve a problem contrary to the numerical solution and retrieve the control parameters of the state equations in which quadratic nonlinear terms are included, and then the dynamical models that can objectively reflect the temporal variation of the regional ozonosphere system are finally established.
文摘Many industrial processes such as heating furnaces have over damping dynamic characteristics. Based on an innovative impulse response model, a method of identification and control for the over damping plant is introduced in the paper. The number of parameters of the model is much less than conventional impulse response model. The model based on tuning procedure of numerical optimum PID controller parameters is presented. For an actual instance, a large scale airflow circulatory resistance furnace control system with cascades of time delays is developed. In the system, the optimum PID control is used in the inner loop. A nonlinear PI compensation control is applied in the outer loop. The coordinating control among each output is realized by a fuzzy control strategy. A process surveillance organization monitors running situation of system and tunes controller parameters.
基金Project supported by the National Natural Science Foundation of China(No.19972059).
文摘A strategy is proposed based on the stochastic averaging method for quasi non- integrable Hamiltonian systems and the stochastic dynamical programming principle.The pro- posed strategy can be used to design nonlinear stochastic optimal control to minimize the response of quasi non-integrable Hamiltonian systems subject to Gaussian white noise excitation.By using the stochastic averaging method for quasi non-integrable Hamiltonian systems the equations of motion of a controlled quasi non-integrable Hamiltonian system is reduced to a one-dimensional av- eraged It stochastic differential equation.By using the stochastic dynamical programming princi- ple the dynamical programming equation for minimizing the response of the system is formulated. The optimal control law is derived from the dynamical programming equation and the bounded control constraints.The response of optimally controlled systems is predicted through solving the FPK equation associated with It stochastic differential equation.An example is worked out in detail to illustrate the application of the control strategy proposed.
