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This study designs an adaptive integrated control. The control system includes two strategies of individual optimal linear quadratic regulator: one to improve vehicle maneuverability and another to improve vehicle stability. The integration is based on the vehicle dynamic variables in the phase plane. The controller can adapt itself by changing gains and integration law as vehicle mass and road friction change. The proper gains and integration law are determined for four special conditions: dry road-curb weight, dry road-gross weight, wet road-curb weight, and wet road-gross weight. These conditions are then expanded for every value of vehicle mass and road friction through fuzzy logic and Sugeno estimator. Simulation results show that considerable improvements are achieved in vehicle dynamic performance through the adaptive integrated control system. [ABSTRACT FROM AUTHOR]

Modern software tools have enhanced modelling, analysis and simulation capabilities pertaining to control of dynamic systems. In this regard, in this paper a full vehicle model with flexible body is exposed by using MSC. ADAMS and MSC. NASTRAN. Indeed, one of the most significant vehicle dynamic controls is directional stability control. In this case, the vehicle dynamic control system (VDC) is used to improving the vehicle lateral and yaw motions in critical manoeuvres. In this paper, for design the VDC system, an optimal control strategy has been used for tracking the intended path with optimal energy. For better performance of VDC system, an anti-lock brake system (ABS) is designed as a lower layer of the control system for maintaining the tyre longitudinal slip in proper value. The performances of the controller on rigid and flexible models are illustrated, and the results show the differences between the control efforts for these models, which are related to the differences of dynamic behaviours of rigid and flexible vehicle dynamic models. [ABSTRACT FROM AUTHOR]