The analytical structure of a typical fuzzy on - off controller that employs three or more triangular Input fuzzy sets, Zadeh fuzzy logic AND operator, fuzzy rules with singleton output fuzzy sets, and the centriod de...The analytical structure of a typical fuzzy on - off controller that employs three or more triangular Input fuzzy sets, Zadeh fuzzy logic AND operator, fuzzy rules with singleton output fuzzy sets, and the centriod defuzzifier is Investigated in this paper. The analytical expressions of the variable gains of the fuzzy controller are derived. The resulting explicit structure shows that the fuzzy controller is accurately a nonlinear PD - like controller with gains continuously changing with system output in different regions of input space.展开更多
Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scal...Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.展开更多
To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output err...To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.展开更多
In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear un...In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.展开更多
To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership functi...To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing （SA） learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived; and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.展开更多
In wind tunnel tests for the full-model fixed with sting,the low structural damping of the long cantilever sting results in destructive low-frequency and large-amplitude vibration.In order to obtain high-quality wind ...In wind tunnel tests for the full-model fixed with sting,the low structural damping of the long cantilever sting results in destructive low-frequency and large-amplitude vibration.In order to obtain high-quality wind tunnel test data and ensure the safety of wind tunnel tests,an energy-fuzzy adaptive PD(Proportion Differentiation)control method is proposed.This method is used for active vibration control of a cantilever structure under variable aerodynamic load excitation,and real-time adjustment of parameters is achieved according to the system characteristics of vibration energy.Meanwhile,a real-time method is proposed to estimate the real-time vibration energy through the vibration acceleration signal,and the average exciting power of aerodynamic load is obtained by deducting the part of the power contributed by the vibration suppressor from the total power.Furthermore,an energy-fuzzy adaptive PD controller is proposed to achieve adaptive control to the changes of the aerodynamic load.Besides,the subsonic and transonic experiments were carried out in wind tunnel,the results revealed that comparing to fixed gain PD controllers,the energy-fuzzy adaptive PD controller maintains higher performance.展开更多
文摘The analytical structure of a typical fuzzy on - off controller that employs three or more triangular Input fuzzy sets, Zadeh fuzzy logic AND operator, fuzzy rules with singleton output fuzzy sets, and the centriod defuzzifier is Investigated in this paper. The analytical expressions of the variable gains of the fuzzy controller are derived. The resulting explicit structure shows that the fuzzy controller is accurately a nonlinear PD - like controller with gains continuously changing with system output in different regions of input space.
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of ChinaProject(05JJ40128) supported by the Natural Science Foundation of Hunan Province, China
文摘Based on the ant colony system （ACS） algorithm and fuzzy logic control, a new design method for optimal fuzzy PID controller was proposed. In this method, the ACS algorithm was used to optimize the input/output scaling factors of fuzzy PID controller to generate the optimal fuzzy control rules and optimal real-time control action on a given controlled object. The designed controller, called the Fuzzy-ACS PID controller, was used to control the CIP-Ⅰ intelligent leg. The simulation experiments demonstrate that this controller has good control performance. Compared with other three optimal PID controllers designed respectively by using the differential evolution algorithm, the real-coded genetic algorithm, and the simulated annealing, it was verified that the Fuzzy-ACS PID controller has better control performance. Furthermore, the simulation results also verify that the proposed ACS algorithm has quick convergence speed, small solution variation, good dynamic convergence behavior, and high computation efficiency in searching for the optimal input/output scaling factors.
文摘To control the robot and track the designed trajectory with uncertain disturbances in a specified precision range, an adaptive fuzzy control scheme for the robot arm manipulator is discussed. The controller output error method （COEM） is used to design the adaptive fuzzy controller. A few or all of the parameters of the controller are adjusted by using the gradient descent algorithm to minimize the output error. COEM is adopted in the adaptive control system for the robot arm manipulator with 5-DOF. Simulation results show the effectiveness of the method and the real time adjustment of the parameters.
文摘In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.
文摘To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing （SA） learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived; and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.
基金co-supported by the project of National Key R&D Program of China(No.2018YFA0703304)the National Natural Science Foundation of China(No.U1808217)Liaoning Revitalization Talents Program of China(No.XLYC1807086)。
文摘In wind tunnel tests for the full-model fixed with sting,the low structural damping of the long cantilever sting results in destructive low-frequency and large-amplitude vibration.In order to obtain high-quality wind tunnel test data and ensure the safety of wind tunnel tests,an energy-fuzzy adaptive PD(Proportion Differentiation)control method is proposed.This method is used for active vibration control of a cantilever structure under variable aerodynamic load excitation,and real-time adjustment of parameters is achieved according to the system characteristics of vibration energy.Meanwhile,a real-time method is proposed to estimate the real-time vibration energy through the vibration acceleration signal,and the average exciting power of aerodynamic load is obtained by deducting the part of the power contributed by the vibration suppressor from the total power.Furthermore,an energy-fuzzy adaptive PD controller is proposed to achieve adaptive control to the changes of the aerodynamic load.Besides,the subsonic and transonic experiments were carried out in wind tunnel,the results revealed that comparing to fixed gain PD controllers,the energy-fuzzy adaptive PD controller maintains higher performance.
