Fuzzy Control for Uncertain Vehicle Active Suspension Systems via Dynamic Sliding-Mode Approach

Observer-Based Fuzzy Integral Sliding Mode Control For Nonlinear Descriptor Systems

“…Applying the established sliding mode control methodology [7], [9], [12], [35], [36] to system (43) involves transformatiom to the nonlinear normal system described bẏ…”

“…Then approaches to systematic analysis and synthesis for the resulting T-S fuzzy systems can be developed within the frame of conventional control technology and fuzzy logic control. As a result, this T-S fuzzy approach has attracted significant attention from the control community [2]- [12]. Despite the superiority of the T-S fuzzy model, the fuzzy rules will exponentially increase with the nonlinearities arising in the system representation.…”

“…Since the nonlinear descriptor system is adopted to represent the mechanical system, the inverse operation of the derivativeterm coefficient of the nonlinear descriptor system is avoided. It is shown that, compared with the existing fuzzy sliding mode control methods [7], [9], [12], the resulting T-S fuzzy system does not contain different input matrices for each local subsystem and the required number of fuzzy rules is consequently markedly reduced. The contributions of this paper are threefold: 1) a systematic way to design an observerbased controller for a T-S fuzzy descriptor system with parameter uncertainties is presented via integral sliding modes; 2) considering that the separation principle is usually not satisfied for T-S fuzzy descriptor systems containing parameter uncertainties [25], [32], in this paper, a single-step approach and two-step approach are respectively proposed to evaluate the observer gains and coefficients in the switching function; 3) based on the proposed methods in this paper, an alternative way to control mechanical systems is presented.…”

Dynamic Characteristics Analysis of Vehicle Incorporating Hydraulically Interconnected Suspension System with Dual Accumulators

“…According to the statistics of National Highway Traffic Safety Administration (NHTSA), 33% of all deaths from passenger vehicle crashes are related to rollover accidents in 2002. As a consequence, research studies on suspension system aiming at improving handling performance and reducing rollover propensity has found prosperity in terms of both active/semiactive controlled and passive suspensions [1][2][3][4][5][6][7][8]. Many active/semiactive control strategies, such as H ∞ control strategies and sliding-mode control strategies, have been utilized onto vehicle to enhance handling performance and ride comfort [9][10][11][12][13][14][15][16].…”

Optimal Disturbance Rejection with Zero Steady‐State Error for Nonlinear Vehicle Suspension Systems under Persistent Road Disturbances

“…In order to avoid the deterioration of ride comfort and even structural damage caused by nonlinear responses, various nonlinear compensation control strategies have been designed for nonlinear vehicle active suspension. An adaptive control scheme was designed for nonlinear vehicle active suspension based on driving state in [13]; an approximation optimal vibration controller for a − fuzzy networked nonlinear vehicle suspension with random actuator time delay was proposed in [5]; a systematic and novel frequency-domain linear feedback control method was established for nonlinear vehicle active suspension by designing the nonlinear characteristic output spectrum in [14]; considering the varying sprung, unsprung masses, and the unknown actuator nonlinearity, a − fuzzy slidingmode control scheme was designed in [15] for nonlinear active suspension vehicle systems; a novel adaptive hybrid controller was designed for a nonlinear vehicle seat suspension based on the sliding-mode controller and ∞ control technique in [16]. While applying the optimal vibration control theory to the nonlinear vehicle active suspension, a Hamilton-Jacobi-Bellman (HJB) equation with no exact analytical solution will be introduced [17][18][19].…”