Networked Multirate Sampling Active Suspension System With Actuator Faults: An IQC-Based Heuristic Fuzzy Static Output Feedback Controller

This article investigates the design problem of a heuristic multirate sampling static output feedback controller for an active suspension system with actuator faults within the constructed integral quadratic constraint framework. First, the Takagi–Sugeno fuzzy model is used to handle the suspension's variable spring-loaded mass, taking into account the uncertainty caused by actuator faults and time delay in the multirate aperiodic sampling process. Second, a novel feedback interconnection form is constructed to constrain uncertain disturbance terms in the active suspension system, accurately scaling the uncertainty operator's norm upper bound, and providing exponential stability criteria for the system. Then, a two-stage heuristic fuzzy multirate sampling static output feedback iterative controller solving algorithm is proposed, which effectively reduces the vehicle body's vertical acceleration while ensuring the suspension deflection and tire load of the vehicle in the presence of actuator faults. Finally, through simulation verification, the proposed heuristic controller can better improve passenger comfort while ensuring driving smoothness and handling stability compared to other control strategies.