Nonlinear Intelligent Control of Two Link Robot Arm by Considering Human Voluntary Components

Abstract

This paper proposes a nonlinear intelligent control of a two link robot arm by considering human voluntary components. In general, human arm viscoelastic properties are regulated in different manners according to various task requirements. The viscoelasticity consists of joint stiffness and viscosity. The research of the viscoelasticity can improve the development of industrial robots, rehabilitation and sports etc. So far, some results have been shown using filtered human arm viscoelasticity measurements. That is, human motor command is removed. As a result, the dynamics of human voluntary component during movements is omitted. In this paper, based on the feedforward characteristics of human multi joint arm, a model is obtained by considering human voluntary components using a support vector regression technique. By employing the learned model, a nonlinear intelligent control of two link robot arm is proposed. Experimental results confirm the effectiveness of this proposal.

Advanced Intelligent Control in Robots

“…The first paper, entitled “Nonlinear Intelligent Control of Two Link Robot Arm by Considering Human Voluntary Components” [ 1 ], investigates a nonlinear intelligent control system of a two-link robot arm by considering the human voluntary components and the feed-forward characteristics of a human multi-joint arm. The proposed feedback controller uses the multi-joint viscoelasticity of the human arm, while the feed-forward controller is based on a support vector machine (SVR), and the stabilization controller is based on operator theory.…”

Passive robust control for uncertain Hamiltonian systems by using operator theory

“…Equivalent one of the system in Figure 4. 24) and (25), in order to satisfy the following conditions, the controllers A* and B* is respectively designed. Hamiltonian systems Σ is robustly stable while the passivity holds for the existing unimodular operator MðwÞ.…”

“…By the increasing requirement of the robust control for the non-linear systems, where the uncertainties usually exist and cannot be completely offset which leads to the unsatisfactory performance, a wider inequality condition is proposed based on the Lipschitz norm proposed in ref. [20], which can be applied in the real systems and thus the method of ORRCF has been widely applied in more and more real systems [21][22][23][24][25][26]. On the existing results of the ORRCF method, another fundamental issue is seldom discussed-the factorisation method, therefore on this topic, we considered it and realised the factorisation of the non-linear plant in refs.…”

Prototype of Automatic Waste Object Picking Robotic Arm in the Working Room

“…These two studies have differences in the control system, where one uses Android as a robotic arm drive, while the other uses IoT, namely the blink application. Continued research [26] entitled "Control of Robotic Arms for the Process of Moving Goods" [13]. This study was created using Arduino uno, plc, and TCS230, which serve as object readers.…”