• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.892-895
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• 1996

An unknown input observer is proposed that can be used in wheelbase preview control of commercial vehicles. The preview and state information, required to calculate actuator force, are reconstructed from the measurement variables such as heave and pitch acceleration. Gain matrix of observer is optimally selected so that influence of system and measurement noises on the estimation error can be minimized. Estimated preview information requires low pass filtering to eliminate high frequency components resulting from differentiation of noisy output signals. Effectiveness of the proposed method is demonstrated by numerical simulation of half car model.

• International Journal of Automotive Technology
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• v.7 no.6
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• pp.749-756
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• 2006

This paper presents a complex stochastic wheelbase preview control method of a motorcycle suspension based on hierarchical modeling method. As usual, a vehicle suspension system is controlled as a whole body. In this method, a motorcycle suspension with five Degrees of Freedom(DOF) is dealt with two local independent 2-DOF suspensions according to the hierarchical modeling method. The central dynamic equations that harmonize local relations are deduced. The vertical and pitch accelerations of the suspension center are treated as center control objects, and two local semi-active control forces can be obtained. In example, a real time Linear Quadratic Gaussian(LQG) algorithm is adopted for the front suspension and the combination of the wheelbase preview and LQG control method is designed for the rear suspension. The results of simulation show that the control strategy has less calculating time and is convenient to adopt different control strategies for front and rear suspensions. The method proposed in this paper provides a new way for the vibration control of multi-wheel vehicles.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.603-610
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• 1998

This paper develops a 7 DOF vehicle model to study the effects of the active suspension on ride. The model is used to derive a control law for the active suspension using a full state linear optimal control technique. A wheelbase preview type active suspension is also considered in the control law derivation. The time delay between wheelbases is approximated using Pade approximation technique. The ride model is extended to a 14 DOF handling model. The 14 DOF handling model includes lateral, longitudinal, yaw and four wheel spin motions in addition to the 7 DOF ride model. A control law which is derived considering only ride related parameters is used to study the effects of the active suspension on a vehicle handling. J-turn maneuver simulation results show that the active suspension has a slower response in lateral acceleration and yaw rate, a bigger steady state lateral acceleration and an oversteer tendency. Lane changing maneuver simulation results show that the active suspension has a little bigger lateral acceleration but a much smaller roll angle and roll motion. Braking maneuver simulation results show that the active suspension has a much smaller pitch angle and pitch motion.