Robust Adaptive Proportional Integral Sliding Mode Control Based on Synthesis of Approximating State Feedback for Robotic Manipulator

D. Mahayana, S. Anwari
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引用次数: 1

Abstract

In this paper, four paradigms are used to deal with a robot manipulator control problem. These paradigms are feedback linearization method, approximating control by Taylor truncation, sliding mode approach, and adaptive proportional integral method. Robotic manipulators are strongly nonlinear, strongly time-varying, and strongly coupled. There are several uncertain factors in robotic manipulator such as dynamic parameters (eg., inertia and payload conditions), dynamical effects (e.g., complex nonlinear frictions), and unmodeled dynamics. The conventional linear controllers are difficult to treat these behaviors. To eliminate this problem, sliding mode control (SMC) can be used as a robust controller. Application of traditional SMC in nonlinear system uses exact feedback linearization. Geometric differential theory is used to develop exact linearization transformation of nonlinear dynamical system, by using nonlinear cancellation and state variable transformation. Hence, the controller can be synthesized by using the standard sliding mode for linear system. The main weak point of the exact linearization is that its implementation is difficult. This study presents a synthesis SMC based on approximating state feedback for robotic manipulator control system. This approximating state feedback is derived from exact feedback linearization. Based on approximating state feedback, sliding mode controller is derived. The original sliding mode control (SMC) has many drawbacks limiting its practical applicability, such as chattering and excessive control input. To eliminate the problems, the discontinuous control signals in the original SMC are replaced by proportional integral (PI) controller. To compensate the uncertainties of the system, the parameters of the PI controller are updated in online manner. To guarantee the stability the knowledge of the system uncertainties is not required. Furthermore, the stability and convergence of the proposed scheme are proved by using Lyapunov like method. To show the effectiveness of the proposed method, the simulation of the proposed sliding mode controller is presented.
基于逼近状态反馈综合的机器人鲁棒自适应比例积分滑模控制
本文采用四种范式来处理机器人机械手的控制问题。这些范例是反馈线性化方法、泰勒截断近似控制、滑模方法和自适应比例积分方法。机器人机械臂是强非线性、强时变和强耦合的。在机械臂中存在着动力学参数(如运动参数)等不确定因素。(惯性和有效载荷条件)、动态效应(如复杂非线性摩擦)和未建模的动力学。传统的线性控制器很难处理这些行为。为了消除这个问题,滑模控制(SMC)可以作为一种鲁棒控制器。传统SMC在非线性系统中的应用采用精确反馈线性化。利用几何微分理论,利用非线性消去和状态变量变换,建立了非线性动力系统的精确线性化变换。因此,可以利用线性系统的标准滑模来合成控制器。精确线性化的主要缺点是难于实现。针对机械臂控制系统,提出了一种基于近似状态反馈的综合SMC控制方法。这种近似状态反馈是由精确反馈线性化得到的。基于近似状态反馈,推导出滑模控制器。原有的滑模控制存在抖振和控制输入过大等缺点,限制了滑模控制的实际应用。为了消除这些问题,将原SMC中的不连续控制信号替换为比例积分(PI)控制器。为了补偿系统的不确定性,采用在线方式更新PI控制器的参数。为了保证系统的稳定性,不需要知道系统的不确定性。此外,利用Lyapunov类方法证明了该方案的稳定性和收敛性。为了验证所提方法的有效性,对所提滑模控制器进行了仿真。
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