Volume 19, Issue 7 (July 2019)                   Modares Mechanical Engineering 2019, 19(7): 1759-1766 | Back to browse issues page

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Rahimi N, Binazadeh T. Distributed Adaptive Robust Controller Design for Consensus in Multi-Agent System Including Robot Arms with Actuator Saturation Constraint. Modares Mechanical Engineering 2019; 19 (7) :1759-1766
URL: http://mme.modares.ac.ir/article-15-21160-en.html
1- Department of Electrical and Electronic Engineering, Shiraz University of Technology
2- Electrical & Electronic Engineering Faculty, Shiraz University of Technology, Shiraz, Iran , binazadeh@sutech.ac.ir
Abstract:   (3286 Views)
In this paper, distributed adaptive robust controller is investigated to solve the leader-follower consensus problem for a multi-agent system consisting of several single-link robot arms. In this approach, each arm is considered as an agent. The dynamical model of each arm contains known and unknown non-linear terms. Unknown terms may be due to parameter uncertainty or simplification of the model. Furthermore, external disturbances are considered in the dynamical equations of each agent. Moreover, the input signal amplitude for each agent should be limited, which is due to the upper bound of the saturation function of the input. In this paper, in order to eliminate the effect of uncertain terms, the adaptive robust approach is used in the design of control laws. In this regard, the upper bounds of uncertain terms are obtained through adaptive laws, which dramatically reduce conservatism. Furthermore, the distributed control laws are designed in such a way that all the agents reach consensus in spite of the uncertain terms and input saturation constraint. The basis of the approach proposed in this paper is based on adaptive sliding mode techniques. For this purpose, suitable sliding surfaces are proposed and distributed adaptive sliding mode controllers are designed. Finally, simulations are presented to confirm the results of theories.
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Article Type: Original Research | Subject: Control
Received: 2018/05/22 | Accepted: 2019/01/13 | Published: 2019/07/1

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