In practice, gain perturbations of controllers which axe caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system wi...In practice, gain perturbations of controllers which axe caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system with constrained inputs, the actual controllers might exceed their limits because of gain perturbations. By the reason, this article considers the problem of resilient predictive control for a class of uncertain time-delay systems. By describing the gain perturbation as a time-varying uncertainty, the sufficient conditions to ensure the closedloop stability and the input constraints are derived. Additionally, an approach to design the resilient predictive controllers is presented in terms of LMI. Finally, the simulation shows that the proposed approach is very effective.展开更多
针对永磁同步电机(permanentmagnetsynchronous motor,PMSM)预测控制系统的模型失配、时变矩阵及观测器增益选择问题,提出基于自适应高增益观测器的预测电流控制方法(predictive current control based on an adaptive high-gain observ...针对永磁同步电机(permanentmagnetsynchronous motor,PMSM)预测控制系统的模型失配、时变矩阵及观测器增益选择问题,提出基于自适应高增益观测器的预测电流控制方法(predictive current control based on an adaptive high-gain observer,AHGOPCC)。通过构建PMSM的前馈型扩张数学模型,集成考虑电机电阻、电感、磁链参数扰动项。提出基于前馈型扩张标称数学模型的高增益观测器,有效跟踪和估计电流与扰动状态及抑制转速变化引起的扰动。同时,设计自适应观测器增益矩阵满足全速工况的高增益条件,简化观测器的增益选择。在此基础上,构建离散化电流模型和成本函数,实现预测电流控制算法。实验结果证明了该方法的有效性,在多种工况下具备更优的快速性、鲁棒性及稳定性。展开更多
Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain sch...Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain schedule. Local LQR control laws and the corresponding maximum control invariant sets can be designed for finite equilibrium points. It is guaranteed that control invariant sets are overlapped each other. The union of the control invariant sets is treated as the terminal constraint set of predictive control. The feasibility and stability of the novel dual-mode model predictive control are investigated with both variable and fixed horizon. Because of the introduction of extended terminal constrained set, the feasibility of optimization can be guaranteed with short prediction horizon. In this way, the size of the optimization problem is reduced so it is computationally efficient. Finally, a simulation example illustrating the algorithm is presented.展开更多
This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher...This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.展开更多
文摘In practice, gain perturbations of controllers which axe caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system with constrained inputs, the actual controllers might exceed their limits because of gain perturbations. By the reason, this article considers the problem of resilient predictive control for a class of uncertain time-delay systems. By describing the gain perturbation as a time-varying uncertainty, the sufficient conditions to ensure the closedloop stability and the input constraints are derived. Additionally, an approach to design the resilient predictive controllers is presented in terms of LMI. Finally, the simulation shows that the proposed approach is very effective.
文摘针对永磁同步电机(permanentmagnetsynchronous motor,PMSM)预测控制系统的模型失配、时变矩阵及观测器增益选择问题,提出基于自适应高增益观测器的预测电流控制方法(predictive current control based on an adaptive high-gain observer,AHGOPCC)。通过构建PMSM的前馈型扩张数学模型,集成考虑电机电阻、电感、磁链参数扰动项。提出基于前馈型扩张标称数学模型的高增益观测器,有效跟踪和估计电流与扰动状态及抑制转速变化引起的扰动。同时,设计自适应观测器增益矩阵满足全速工况的高增益条件,简化观测器的增益选择。在此基础上,构建离散化电流模型和成本函数,实现预测电流控制算法。实验结果证明了该方法的有效性,在多种工况下具备更优的快速性、鲁棒性及稳定性。
基金Supported by National Natural Science Foundation of P. R. China (60474051, 60534020)Development Program of Shanghai Science and Technology Department (04DZ11008)the Program for New Century Excellent Talents in Universities of P. R. China (NCET)
文摘Aiming at a class of nonlinear systems with multiple equilibrium points, we present a dual-mode model predictive control algorithm with extended terminal constraint set combined with control invariant set and gain schedule. Local LQR control laws and the corresponding maximum control invariant sets can be designed for finite equilibrium points. It is guaranteed that control invariant sets are overlapped each other. The union of the control invariant sets is treated as the terminal constraint set of predictive control. The feasibility and stability of the novel dual-mode model predictive control are investigated with both variable and fixed horizon. Because of the introduction of extended terminal constrained set, the feasibility of optimization can be guaranteed with short prediction horizon. In this way, the size of the optimization problem is reduced so it is computationally efficient. Finally, a simulation example illustrating the algorithm is presented.
文摘This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.