In this paper, a robust model predictive control approach is proposed for a class of uncertain systems with time-varying, linear fractional transformation perturbations. By adopting a sequence of feedback control laws...In this paper, a robust model predictive control approach is proposed for a class of uncertain systems with time-varying, linear fractional transformation perturbations. By adopting a sequence of feedback control laws instead of a single one, the control performance can be improved and the region of attraction can be enlarged compared with the existing model predictive control (MPC) approaches. Moreover, a synthesis approach of MPC is developed to achieve high performance with lower on-line computational burden. The effectiveness of the proposed approach is verified by simulation examples.展开更多
A model of uncertain switched fuzzy systems whose subsystems are uncertain fuzzy systems is presented. Robust controllers for a class of switched fuzzy systems are designed by using the Lyapunov function method. Stabi...A model of uncertain switched fuzzy systems whose subsystems are uncertain fuzzy systems is presented. Robust controllers for a class of switched fuzzy systems are designed by using the Lyapunov function method. Stability conditions for global asymptotic stability are developed and a switching strategy is proposed. An example shows the effectiveness of the method.展开更多
A novel variable structure control (VSC) strategy with a dynamic disturbance compensator based on the reaching law for a class of uncertain discrete systems is presented. The robust stability to disturbance and the sy...A novel variable structure control (VSC) strategy with a dynamic disturbance compensator based on the reaching law for a class of uncertain discrete systems is presented. The robust stability to disturbance and the system dynamics in the vicinity of the switching plane are studied. A measure of the uncertain parameters and external disturbance is obtained through delaying every sampling time. Theoretical analysis and experimental simulation results demonstrate that the dynamic performance and robustness of the closed-loop system are improved effectively.展开更多
Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-d...Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure.The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots.However,there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion.As a result,the mobile robot has lim-ited performance,such as chattering during curved movement.In this research work,a three-tiered adaptive robust control with fuzzy parameter estimation,including dynamic modeling,direct torque control and wheel slip control is pro-posed.Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller(ARC)parameters and tracking the trajectories with less tracking error as well as high tracking accuracy.This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique.Our suggested approach outperforms the existing control methods such as Fuzzy,proportional–integral–derivative(PID)and adaptive robust controller with discrete projection(ARC–DP).The experimental results show that the scheduled performance index decreases by 2.77%and 4.76%.All the experimen-tal simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.展开更多
Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics,random disturbances and load variations.To account for uncertain disturbances in the operation of manipulators,we ...Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics,random disturbances and load variations.To account for uncertain disturbances in the operation of manipulators,we propose an adaptive manipulator control method based on a multi-joint fuzzy system,in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable.The control algorithm of the system is a MIMO(multi-input-multi-output)fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error.It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required.Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity,coupling and uncertainty.Therefore,the proposed algorithm has good practical application prospects and promotes the development of complex control systems.展开更多
Engine-variable pump-variable motor drive system is a complex nonlinear system. In order to improve system response speed and stability,a sliding-mode variable-structure control based on a feedback linearization theor...Engine-variable pump-variable motor drive system is a complex nonlinear system. In order to improve system response speed and stability,a sliding-mode variable-structure control based on a feedback linearization theory is analyzed in this research. A standardized system model is established and linearized by the feedback linearization theory,and the input dimension is reduced through the relationship between variables which has simplified the linearization process. Then the sliding-mode controller using an exponential reaching law is designed and the Lyapunov stability of this algorithm is verified. The simulation results show that the sliding-mode variable-structure controller based on the feedback linearization theory can improve system response speed,reduce overshoot and achieve stronger robustness,so the vehicle speed control requirements can be satisfied well.展开更多
基金supported by National Natural Science Foundation of China (No. 60934007, No. 61074060)China Postdoctoral Science Foundation (No. 20090460627)+1 种基金Shanghai Postdoctoral Scientific Program (No. 10R21414600)China Postdoctoral Science Foundation Special Support (No. 201003272)
文摘In this paper, a robust model predictive control approach is proposed for a class of uncertain systems with time-varying, linear fractional transformation perturbations. By adopting a sequence of feedback control laws instead of a single one, the control performance can be improved and the region of attraction can be enlarged compared with the existing model predictive control (MPC) approaches. Moreover, a synthesis approach of MPC is developed to achieve high performance with lower on-line computational burden. The effectiveness of the proposed approach is verified by simulation examples.
基金the National Natural Science Foundation of China(No.60574013, 60274009).
文摘A model of uncertain switched fuzzy systems whose subsystems are uncertain fuzzy systems is presented. Robust controllers for a class of switched fuzzy systems are designed by using the Lyapunov function method. Stability conditions for global asymptotic stability are developed and a switching strategy is proposed. An example shows the effectiveness of the method.
基金Funded by the Natural Science Foundation of China (No.60274020 and 69974017) Hebei Natural Science Foundation (No. 602621) and Guangxi Natural Science Foundation (No. 0135065).
文摘A novel variable structure control (VSC) strategy with a dynamic disturbance compensator based on the reaching law for a class of uncertain discrete systems is presented. The robust stability to disturbance and the system dynamics in the vicinity of the switching plane are studied. A measure of the uncertain parameters and external disturbance is obtained through delaying every sampling time. Theoretical analysis and experimental simulation results demonstrate that the dynamic performance and robustness of the closed-loop system are improved effectively.
文摘Four-wheeled,individual-driven,nonholonomic structured mobile robots are widely used in industries for automated work,inspection and explora-tion purposes.The trajectory tracking control of the four-wheel individual-driven mobile robot is one of the most blooming research topics due to its nonholonomic structure.The wheel velocities are separately adjusted to follow the trajectory in the old-fashioned kinematic control of skid-steered mobile robots.However,there is no consideration for robot dynamics when using a kinematic controller that solely addresses the robot chassis’s motion.As a result,the mobile robot has lim-ited performance,such as chattering during curved movement.In this research work,a three-tiered adaptive robust control with fuzzy parameter estimation,including dynamic modeling,direct torque control and wheel slip control is pro-posed.Fuzzy logic-based parameter estimation is a valuable tool for adjusting adaptive robust controller(ARC)parameters and tracking the trajectories with less tracking error as well as high tracking accuracy.This research considers the O type and 8 type trajectories for performance analysis of the proposed novel control technique.Our suggested approach outperforms the existing control methods such as Fuzzy,proportional–integral–derivative(PID)and adaptive robust controller with discrete projection(ARC–DP).The experimental results show that the scheduled performance index decreases by 2.77%and 4.76%.All the experimen-tal simulations obviously proved that the proposed ARC-Fuzzy performed well in smooth groud surfaces compared to other approaches.
基金the project of science and technology of Henan province under Grant No.14210221036.
文摘Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics,random disturbances and load variations.To account for uncertain disturbances in the operation of manipulators,we propose an adaptive manipulator control method based on a multi-joint fuzzy system,in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable.The control algorithm of the system is a MIMO(multi-input-multi-output)fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error.It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required.Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity,coupling and uncertainty.Therefore,the proposed algorithm has good practical application prospects and promotes the development of complex control systems.
基金Supported by the National Natural Science Foundation of China(No.51275126)the China Aerospace Science and Technology CorporationHarbin Institute of Technology Joint Technical Innovation Center Fund Project(CASC-HIT15-1A04)
文摘Engine-variable pump-variable motor drive system is a complex nonlinear system. In order to improve system response speed and stability,a sliding-mode variable-structure control based on a feedback linearization theory is analyzed in this research. A standardized system model is established and linearized by the feedback linearization theory,and the input dimension is reduced through the relationship between variables which has simplified the linearization process. Then the sliding-mode controller using an exponential reaching law is designed and the Lyapunov stability of this algorithm is verified. The simulation results show that the sliding-mode variable-structure controller based on the feedback linearization theory can improve system response speed,reduce overshoot and achieve stronger robustness,so the vehicle speed control requirements can be satisfied well.
基金National Natural Science Foundation of China(No.61903291)Special Scientific Research Project of Shaanxi Provincial Department of Education(No.21JK0732)。