MIMO非线性自适应模糊滑模控制

为了解决传统的自适应模糊滑模控制方法需经无穷长时间才能达到平衡点，不能对系统进行精确地跟踪控制的问题。提出一种具有快速收敛性的自适应模糊滑模控制方法。控制器用具有快速收敛性和稳定性的最终吸引子做自适应模糊调节率代替传统自适应模糊调节率，不仅具有稳定性且具有快速收敛性，从而使控制系统的输出能在有限时间内精确地跟踪参考信号。证明了所设计控制器是全局稳定的。并用该方法控制了二自由度机器手系统，仿真结构表明该方法能使机器手在有限时间内达到精确的位置和速度，从而证实了其快速性。

Adaptive fuzzy sliding mode control based on terminal attractors for multi-input multi-output nonlinear systems

This paper presents a sliding mode control scheme using adaptive fuzzy systems with terminal attractors for a class of uncertain multi input multi output (MIMO) nonlinear systems. The traditional adaptive fuzzy sliding mode control systems can only converge to the arbitrary small neighborhood of zero in infinite time which makes system can not track desired signals accurately. Therefore, the traditional method is not suitable for controlling many nonlinear systems, for example, the accurate position control of many robot systems in short time, which shows that it is important to develop a controller which converges rapidly. In this paper, the proposed controller utilizes an adaptive fuzzy learning rule with terminal attractors having property of rapidity and stability to replace the traditional adaptive fuzzy learning rule, which guarantees the stability and fast convergence of control systems, so the output of nonlinear systems can trace the given input reference signal accurately in finite time. Then, global stability of the controller is established. Finally, the proposed method is used to control a two degree of freedom robotic manipulator, and the results of the simulation demonstrate the robotic manipulator can track the desired position and speed accurately in finite time which illustrates the rapidity of the proposed method.