In this study, an adaptive fuzzy inverse optimal control problem is investigated for a class of vehicle active suspension systems. Since active suspension systems have dynamic characteristics of complexities and spring non-linearities, the fuzzy logic systems are utilised to learn the unknown non-linear dynamics. In addition, there exist the constraints of the displacements of the sprung and unsprung masses, vertical vibration speeds, and current intensity in the considered suspension system, therefore, the Barrier Lyapunov functions are introduced into the control design to ensure that the full-state constraints are not overstepped. The inverse optimal control method is adopted by constructing an auxiliary system, which circumvents the assignment of solving a Hamilton–Jacobi–Bellman equation and brings about an inverse optimal controller associated with a meaningful objective functional. Based on Lyapunov stability theory and backstepping recursive design algorithm, a fuzzy adaptive optimal control scheme is developed. It is proved that the proposed control scheme not only guarantees that the vertical vibration of the vehicle is stabilised by the electromagnetic actuator but also achieves the goal of inverse optimality with regard to the cost functional. Finally, the simulation studies check the validity of the presented control strategy.
Adaptive fuzzy optimal control for a class of active suspension systems with full-state constraints
IET Intelligent Transport Systems ; 14 , 5 ; 371-381
01.11.2019
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
fuzzy adaptive optimal control scheme , auxiliary system , control system synthesis , road vehicles , Lyapunov methods , vehicle active suspension systems , inverse optimal control method , optimal control , full-state constraints , inverse optimality , nonlinear dynamics , control nonlinearities , vertical vibration speeds , Barrier Lyapunov functions , fuzzy logic systems , fuzzy control , spring nonlinearities , inverse optimal controller , nonlinear control systems , adaptive fuzzy inverse optimal control problem , suspensions (mechanical components) , adaptive control , control design
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