Chang Yeong-Chan
Department of Electrical Engineering, Kun-Shan University of Technology, Tainan Hsien, Taiwan.
IEEE Trans Syst Man Cybern B Cybern. 2005 Dec;35(6):1108-19. doi: 10.1109/tsmcb.2005.850149.
This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.
本文研究了为一大类不确定非线性时变系统设计基于自适应模糊（或基于神经网络）的鲁棒控制器的问题。这类系统可能受到对象不确定性、未建模扰动和外部干扰的影响。结合自适应控制技术和变结构控制技术的非线性H∞控制技术被用于构造智能鲁棒镇定控制器，从而实现H∞控制。通过不确定机器人系统的鲁棒跟踪控制设计问题来证明所提出的鲁棒镇定控制方案的有效性。因此，在存在高度不确定性的情况下，不确定机器人系统的智能鲁棒跟踪控制器能够很容易地实现。其求解仅需解决一个线性代数矩阵不等式，并且能够保证令人满意的暂态和渐近跟踪性能。通过一个仿真例子来验证所提出控制算法的性能。
