Non-fragile control design and state estimation for vehicle dynamics subject to input delay and actuator faults

• Published in: IET control theory & applications Vol. 14; no. 1; pp. 134 - 144
• Main Authors: Sakthivel, Rathinasamy, Mohanapriya, Saminathan, Kaviarasan, Boomipalagan, Ren, Yong, Anthoni, Selvaraj Marshal
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 01.01.2020
• Subjects: actual state values; actuator faults; actuators; asymptotic stability; considered vehicle model; control system synthesis; critical situations; delays; estimated state values; extended dissipative theory; formulated LMI‐based conditions; fuzzy control; input delay; input time delay; linear matrix inequalities; Lyapunov methods; nonfragile controller; nonfragile reliable control design method; Research Article; robust control; state estimation; state estimator‐based nonfragile reliable control design; sufficient conditions; Takagi–Sugeno fuzzy model; time‐varying systems; T‐S fuzzy control system; uncertain systems; vehicle dynamics; vehicle rollover; time-varying systems; asymptotic stability; nonfragile controller; fuzzy control; extended dissipative theory; sufficient conditions; actuators; linear matrix inequalities; robust control; actual state values; T-S fuzzy control system; Takagi–Sugeno fuzzy model; vehicle rollover; actuator faults; uncertain systems; state estimator-based nonfragile reliable control design; vehicle dynamics; control system synthesis; estimated state values; critical situations; considered vehicle model; input time delay; formulated LMI-based conditions; delays; state estimation; input delay; nonfragile reliable control design method; Lyapunov methods
• DOI: 10.1049/iet-cta.2018.5967
• ISSN: 1751-8644

In this study, the authors precisely concentrate on the issue of state estimator-based non-fragile reliable control design of the vehicle dynamics in critical situations via the extended dissipative theory. In particular, the vehicle dynamics for rollover mitigation with input time delay and the state estimator are represented by the Takagi–Sugeno (T-S) fuzzy model. Moreover, by constructing a suitable Lyapunov–Krasovskii functional, sufficient conditions for asymptotic stability and extended dissipativity of the proposed T-S fuzzy control system are formulated in terms of linear matrix inequalities (LMIs) such that the estimated state values are exactly synchronised with the actual state values of the considered vehicle model. Also, a non-fragile reliable control design method is then presented via the formulated LMI-based conditions, which can satisfactorily prevent the vehicle rollover in critical situations. Finally, the proposed theoretical results are verified through simulations wherein the significance and importance of the designed non-fragile controller are clearly illustrated.