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In this paper, the Kalman filter algorithm is used to design a practical adaptive control strategy. The adaptation is intended to adjust the system operation according to the changes of road input. A moderate adaptive time of at least 3 seconds is used. Limit stops are added to prevent the increase in the wheel travel behind the specified limit. The active suspension feedback system is designed based on measuring only the suspension displacement. A gain scheduling adaptive scheme which consists of four sets of state feedback gains is designed. The estimation process of dynamic tyre deflection and other necessary state variables through the Kalman filter is illustrated. Among other things, this estimate is used to derive the gain scheduling adaptive scheme. The strategy is applied to a quarter car active suspension system. Results are generated at a constant speed on random road profiles.

Integral Control strategy for vehicle chassis systems had been of great interest for vehicle designers in the last decade. This paper represents the interaction of longitudinal control and lateral control. In other words the traction control system and handling control system. Definitely, tire properties are playing a vital role in such interaction as it is responsible for the generated forces in both directions. A seven degrees of freedom half vehicle model is derived and used to investigate this interaction. The vehicle body is represented as a rigid body with three degrees of freedom, lateral and longitudinal, and yaw motions. The other four degrees are the two rotation motion of the front wheel and the rear wheel. This two motions for each wheel are spin motion and the steering motion. The traction controller is designed to modulate engine torque through adjusting the throttle angle of the engine upon utilized adhesion condition at the driving road wheels.