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This paper presents a robust output feedback control design for a half-car active suspension system by considering driver's biodynamics. Because of different kinds of passengers there is a wide range of variations in biodynamics' parameters, and an appropriate robust control design approach, μ-synthesis approach, is used to tackle these parametric uncertainties. The performance of active suspension system with designed controller is compared with the open loop one in both frequency and time domain simulations. The results show that μ-synthesis based controller achieves great performance in ride comfort. In addition, suspension deflections, road holding and actuators force remain in reasonable regions. Finally, analysis of robust performance indicating that the μ-synthesis controller remains stable in a wide range of frequency domain despite parametric uncertainties, which is also validated by a specific case in this paper.

Active vibration suppression of a simply supported, arbitrarily thick, transversely isotropic circular cylindrical host panel, integrated with spatially distributed piezoelectric actuator and sensor layers, is investigated based on the linear three dimensional exact piezo-elasticity theory. To assist control system design, system identification is conducted by applying a frequency domain subspace approximation method based on N4SID algorithm using the first few structural modes of the system. The state space model is constructed from system identification and used for state estimation and development of control algorithm. The optimal electrode configuration for the collocated piezoelectric actuator-sensor pair is found by applying a genetic optimization procedure based on maximization of a quantifiable objective function considering the controllability, observability and spillover prevention of the identified system. A linear quadratic Gaussian (LQG) optimal controller is subsequently designed and simulated based on the identified model of optimally configured smart structure in order to actively control the system response in both frequency and time domains. The dynamic performance and effectiveness of the optimized vibration control system is demonstrated for two different types of external mechanical excitations (i.e., impulsive load and white noise disturbance). The accuracy of dynamic analysis is established with the aid of a commercial finite element package and the data available in the literature.

This paper investigates the vibration control of geometrically nonlinear beam with Macro Fiber Composite (MFC) actuators using two different adaptive control algorithms. A complete mathematical modeling is presented in order to find the dynamic equation of motion. Then, a robust adaptive fuzzy control algorithm for controlling the proposed mechanical structure is introduced. This controller includes a fuzzy scheme and a robust controller. Based on sliding mode controller a fuzzy system is introduced to mimic an ideal controller. The robust controller is designed based on compensation of the difference between the fuzzy controller and the ideal controller. The parameters of the fuzzy system and uncertainty bound of the robust controller are adjusted adaptively. The adaptive laws are designed based on the Lyapunov stability theorem to reach the stability of the closed-loop system. Meanwhile, for comparison purposes the presented controller is compared with self tuning Ziegler-Nichols PID controller for both robustness and vibration suppression performance aspects. Effectiveness of these two control strategies is evaluated by numerical simulations. Detailed analysis for the closed-loop system is carried out to evaluate the vibration controlling performance under different output excitation, robustness of the closed-loop system under sudden loading and the effect of initial condition on vibration characteristic.