Efficient reaching law for SMC with PID surface applied to a manipulator

Pranav, J. Kumar, V. Kumar, K. Rana
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引用次数: 6

Abstract

Robotic manipulators are employed in various applications like pick and place, painting and welding etc. In these applications it is required to track a predefined trajectory. For the same an efficient controller is required as the manipulator is a nonlinear complex and coupled system. Due to nonlinearities and coupling effect, the design of an ideal controller has been a challenging task. This paper presents a comparative study of sliding mode control (SMC) with proportional, integral, and derivative sliding surface with three different reaching laws, namely, constant rate, exponential and power rate reaching law to control a two-link robotic manipulator. All the three cases for different reaching laws are investigated for trajectory tracking, disturbance rejection and mass uncertainty. The control parameters for SMC and boundary layer are tuned with Genetic Algorithm optimization technique. Simulation results show that the power rate reaching law offers better performance than the other two laws for disturbance rejection and mass uncertainties, whereas all the three laws performed equally well for set-point tracking.
将带PID曲面的SMC有效逼近律应用于机械手
机械手应用于各种场合,如取放、喷漆、焊接等。在这些应用程序中,需要跟踪预定义的轨迹。由于机械手是一个复杂的非线性耦合系统,因此需要一个有效的控制器。由于非线性和耦合效应,理想控制器的设计一直是一项具有挑战性的任务。本文对具有比例、积分和导数三种不同趋近律的滑模控制(SMC),即恒速率、指数和功率速率趋近律,控制双连杆机器人机械手进行了比较研究。研究了三种不同到达律下的轨迹跟踪、扰动抑制和质量不确定性。采用遗传算法优化技术对SMC和边界层的控制参数进行了调整。仿真结果表明,功率趋近律在抑制干扰和质量不确定性方面的性能优于其他两种律,而三种律在设定点跟踪方面的性能相同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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