Journal of Intelligent & Fuzzy Systems 38 (2020) 4173–4190 DOI:10.3233/JIFS-190531 IOS Press 4173 Distributed adaptive output-feedback fault tolerant control for nonlinear systems with sensor faults Jianye Gong a , Bin Jiang b and Qikun Shen a,∗ a College of Information Engineering, Yangzhou University, Yangzhou, China b College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China Abstract. This paper studies the distributed adaptive output-feedback fault tolerant control problem for leader-following multiagent systems with sensor faults. By using the approximation theory of neural networks, an unknown continuous function is approximated, and the problem that the neural network output deviates from the true approximation of the unknown function due to the faults of neural network input is solved. A filter observer is adopted to estimate the unmeasurable states. Based on the adaptive backstepping technique and fault tolerant control technique, a distributed adaptive neural output-feedback control scheme is proposed to guarantee the output consensus of all nodes under directed communication graphs. Based on graph theory and Lyapunov stability theory, it is proved that the proposed adaptive neural control scheme guarantees the uniformly ultimate boundness of the closed-loop systems, and the tracking errors converge to a small adjustable neighborhood of the origin. The simulation results demonstrate the effectiveness of the control approach in this paper. Keywords: Fault tolerant control, adaptive control, multiagent systems 1. Introduction During the past decades, studies on the topic of distributed cooperative control of multiagent systems have received increasing attention, mainly due to its widespread application in the field of production and engineering, such as mobile robots, unmanned air vehicles flying, power systems, etc. [1–5]. For multiagent systems, one of the fundamental research problem is consensus, which has been studied exten- sively. Consensus can be roughly categorized into two forms, i.e., leaderless consensus and leader-following consensus. Many researches have been done for the cooperative control problem of multiagent systems ∗ Corresponding author. Qikun Shen, College of Information Engineering, Yangzhou University, Yangzhou, China. E-mail: qkshen@yzu.edu.cn. [3–6]. In [6], adaptive synchronization controllers were designed for distributed systems having non- identical unknown nonlinear dynamics. In [7], a practical design method was proposed for cooperative tracking control of high-order nonlinear multiagent systems with a dynamic leader. It should be noted that adaptive fuzzy or neural net- work (NN) control schemes have played an important role to solve the uncertain nonlinearities in modern control theory [7–12]. In the past decades, a vari- ety of adaptive cooperative control approaches have been proposed for multiagent systems [8–12]. In [8], a NN-based adaptive approach was developed for the leader-following control for multiagent systems with uncertain dynamics and external disturbances. In [9], the cooperative control problems of nonlinear multiagent systems with unmodeled dynamics were investigated, and a distributed neural-networks-based ISSN 1064-1246/20/$35.00 © 2020 – IOS Press and the authors. All rights reserved