| Active control for vehicle suspension is one of the important research subjects in vehicle dynamics, automobile design and manufactures. This paper focuses on studying the control algorithm of the active suspension. The effects of system parameters, e.g. stiffness, damping coefficient of a suspension on suspension dynamics are studied comprehensively, thus they are used on the assessment for active-suspension design. In this paper, a quarter car mathematical model of two-DOF has been set up, different control schemes have been applied and simulatedrespectively including sky-hook control, self-correcting control, fuzzy control and Adaline neural networks control, by means of the control simulation software-Matlab6.1+Simulink for Windows. The computer simulation results show that the control algorithm used can reduce the root mean square value of car body acceleration and the root mean square value of suspension dynamic deflection, andthe dynamic load doesn't vary much, so the ride quality can be greatly improved. The above research results will be valuable to the further studying of suspension theory and the suspension testing future.In chapter 1, a survey of suspension home and abroad has been discussed firstly. Then the contents of the thesis and the means of the research are put forward.In chapter 2, the performance indexes are determined, which are the root mean square value of car body acceleration, the root mean square value of suspension dynamic deflection, and the root mean square value of suspension dynamic load. A quarter car mathematical model of two-DOF has been set up, the dynamic characteristic property of the suspension is researched. Then the suspensionsimulation model is set up by means of the software-Simulink. All the controlschemes will use this simulation model.In chapter 3, the typical control scheme of active-suspension which is called sky-hook control is researched . The feedback coefficient of sky-hook control is defined on the basis of the random control theory . The simulation results show that the root mean square value of car body acceleration and the root mean square value of suspension dynamic deflection are reduced.In chapter 4, the control scheme of active-suspension which is called self-correcting control is researched . It is necessary and significant for the relevant control system to possess of adaptability for achieving fairly good vibration isolating effectiveness in various working conditions of suspension which is a typical time-varying system. Algorithms of parameter estimation of memory attenuation,recursion and least two multiply and self-correcting control of proportion and least root mean square are applied . The numerical simulation results show that the adaptive control scheme is applicable due to its good adaptability for automotive suspensions with a number of time-varying parameters.In chapter 5, the control scheme of active-suspension which is called fuzzy control is researched . The control feedback quantity is the suspension dynamic deflection. The input of the fuzzy controller is the suspension dynamic deflection and its change. The fuzzy control law is defined on the basis of the experience, and thefuzzy control table off-line is set up. The quantity factor is defined on the basis of the suspension dynamic deflection, and the proportional factor is defined on the basis of the control effectiveness. Then the law-correcting fuzzy control is setup. The fuzzy control law is corrected by correcting the correction factor. The simulation results show that the fuzzy control scheme based on experience can reduce the root mean square value of car body acceleration greatly, and the control effectiveness of the law-correcting fuzzy control scheme is better than that of the fuzzy control scheme based on experience.In chapter 6, the control scheme of active-suspension which is called Adaline neural networks control is researched . Firstly the suspension parameters are identified by using the Adaline neural networks, then the co...
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