Event-based Robust Control Techniques for Wheel-Based Robots Under Cyber-attack and Dynamic Quantizer

Saeedi, Mobin and Zarei, Jafar and Seif, Mehrdad and Montazeri, Allahyar (2022) Event-based Robust Control Techniques for Wheel-Based Robots Under Cyber-attack and Dynamic Quantizer. In: Mobile Robots : Motion Control and Path Planning. Studies in Computational Intelligence . Springer Nature, Cham. (In Press)

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Abstract

Nowadays, mobile robots are becoming an increasingly significant part of daily human life. Humanoid robots, wheeled mobile robots, aerial vehicles, mobile manipulators, and more are examples of mobile robots. As opposed to other robots, they are capable of moving autonomously, with sufficient intelligence to make decisions in response to the perceptions they receive from their environment. In today’s world, cooperative tasks and the ability to control robots via networks make them a component of cyber-physical systems (CPSs). In this study, mobile robots that are acting as a part of CPSs are examined. Data-network burden, signal quantizers, cyber security, delayed transition, and robust performance are some of the challenges they face. A total of three sections are then devoted to addressing these issues in detail. As a first step, the governing equation for mobile robots is explained, and then their robust and resilient behavior of them is examined by establishing the event-based adaptive optimal fast terminal sliding mode control (AOFTSMC) approach for nonlinear uncertain dynamic systems that are subjected to denial-of service (DoS) cyber attacks. In this case, it is assumed that the conveyed signal is being corrupted randomly by an attacker. In this situation, it is essential to design the closed-loop controller parameters in such a way that the performance can be maintained under malicious attacks while the communication resources are preserved. Due to the unrealistic nature of delayed-free communication, the stability analysis is conducted for a general form of uncertain nonlinear delayed input dynamic systems. The quantization effect on the closed-loop control system is then analyzed in conjunction with robust behavior and event-based data transmission. A novel criterion is established to adjust dynamic quantizers’ parameters according to the variation of event-triggering error, enabling the quantizer to be more accurate and facilitating implementation procedures. Finally, simulation results validate the presented methodology.