A Cognitive Control Approach for Networked Control Systems with Random Packet Losses. Issue 11 (4th October 2021)

• Record Type: Journal Article
• Authors: Wang, Shuti; Yin, Xunhe; Li, Peng; Wang, Xin; Wang, Ge; Hu, Jiankun
• Is Part Of: Advanced theory and simulations. Volume 4:Issue 11(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-10-04
• Subjects: backstepping control -- hybrid cognitive control -- information entropy -- information gap -- networked control systems -- Q‐learning -- random packet losses; Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.202100163
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract: This paper presents a novel hybrid cognitive control method inspired by human brain mechanism for networked control systems (NCSs) with random packet dropouts. The random packet losses are assumed to occur in both channels from sensor to controller and from controller to actuator. Different from most of the existing studies, the information entropy is utilized to characterize the uncertainties of the random packet dropouts. A hybrid cognitive control model is designed for NCSs subject to random packet losses. More specifically, the proposed hybrid cognitive control algorithm is constructed by using the Q‐learning and backstepping control simultaneously. That is, the Q‐learning is employed for the cognitive controller to regulate the backstepping controller and meantime act on the control object. In addition, the information gap is defined based on the information entropy, and used for depicting the uncertainties of the random packet dropouts. Simulation results are performed to validate the designed hybrid cognitive control method, demonstrating that it can eliminate the effects of packet losses and thus performs better than the traditional backstepping or proportional‐integral‐derivative (PID) controllers. Abstract : A novel hybrid cognitive control is designed by blending the Q‐learning with backstepping control for networked control systems under random packet dropouts of both channels between sensor to controller and controller to actuator. The cognitive controller can not only manage the backstepping controller according to the case of packet losses, but also can control the plant.