Adaptive Control of Large-Scale Soft Robot Manipulators With Unknown Payloads

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS

Mechatronic Systems and Control Pub Date : 2019-11-26 DOI:10.1115/dscc2019-9037

J. S. Terry, J. Whitaker, R. Beard, Marc D. Killpack

引用次数: 2

Abstract

The compliance and other nonlinear dynamics of large-scale soft robots makes effective control difficult. This is especially true when working with unknown payloads or when the system dynamics change over time which is likely to happen for soft robots. In this paper, we present a novel method of coupling model reference adaptive control (MRAC) with model predictive control (MPC) for platforms with antagonistic pneumatic actuators. We demonstrate its utility on a fully inflatable, six degree-of-freedom pneumatically actuated soft robot manipulator that is over two meters long. Specifically, we compare control performance with no integral controller, with an integral controller, and with MRAC when running a nominal model predictive controller with significant weight attached to the end effector.

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具有未知载荷的大型软机械臂自适应控制

大型软体机器人的柔顺性等非线性动力学特性给有效控制带来了困难。在处理未知的有效载荷或系统动力学随时间变化的情况下，这一点尤其正确，这可能发生在软机器人身上。针对具有对抗性气动执行器的平台，提出了一种模型参考自适应控制(MRAC)与模型预测控制(MPC)耦合的新方法。我们在一个超过两米长的全充气、六自由度气动驱动的软机器人机械手上展示了它的实用性。具体而言，我们比较了无积分控制器、积分控制器和MRAC在运行标称模型预测控制器时的控制性能，并将显著权重附加到末端执行器上。

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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来源期刊

Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.40

自引率

66.70%

发文量

期刊介绍： This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.