Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

基于模型降阶与链式结构的平面欠驱动机械臂位姿控制

针对第三关节为被动的平面四连杆(active-active-passive-active,简称AAPA)欠驱动机械臂的位姿控制问题,提出一种基于模型降阶与链式结构的控制策略.整个控制过程被划分为3个阶段.第1阶段,通过控制第四连杆的角度至零,将平面AAPA机械臂降阶为平面虚拟四连杆(active-activepassive,简称AAP)欠驱动机械臂.第2阶段,首先将平面虚拟AAP机械臂的模型转换为标准链式结构形式.然后,设计相应的控制器将平面虚拟AAP机械臂的被动关节控制至其目标位置,同时,将被动连杆的姿态角控制至中间姿态角,从而将平面AAPA机械臂进一步降阶为平面Acrobot.第3阶段,控制平面Acrobot驱动连杆的角度至其目标角度,连带实现对被动连杆的角度控制,最终实现平面AAPA机械臂的位姿控制目标.考虑到平面Acrobot存在角度约束,因此,利用遗传算法协调与优化被动关节的目标位置、被动连杆的中间姿态角、第四连杆的目标角度与被动连杆的目标姿态角,确保平面Acrobot对于系统目标位姿的目标角度解存在.最后,通过仿真验证控制策略的有效性.