Design Of LQG Controller For Suspension Systems

With the development of automotive suspension technology,people put forward higher requirements on the performance of cars,such as ride comfort and handling stability.The active suspension system can dynamically adjust the stiffness and damping of the suspension according to the different driving conditions and makes the suspension system always be in the best damping state.The performance of semi-active suspension system is better than the passive suspension and the cost is lower than the active suspension.Whether it is active suspension or semi-active suspension system,the key to its design is to select the right control strategy which can provide good performance for vehicles.In recent years,many experts and scholars have done a lot of research about the selection of the control strategy and put forward a number of different control methods.Wherein the linear quadratic and Gaussian distributed(LQG)control theory is widely used.This paper takes the 4-DOF active suspension system and the magnetorheological semi-active suspension system as the research object and carries out the design of LQG controller for vehicle suspension system and other related research work based on the linear quadratic optimal control theory,as follows,(1)Design of LQG controller for 4-DOF active suspension system considering the feedback of road input signalsFirstly,the weighting coefficients of the LQG controller are determined by the analytic hierarchy process and improved analytic hierarchy process,respectively.On the basis of these two methods,the weighting coefficients of the performance indexes are optimized by genetic algorithm.The weighting coefficients of the LQG controller are applied to the active suspension system respectively,and the simulation results show that these three methods can achieve similar optimization effect on the performance evaluation index of the active suspension system in determining the weighting coefficients.Compared with the analytic hierarchy process and the improved analytic hierarchy process,the genetic algorithm avoids the problem of inconsistency for the performance indexes caused by the subjective judgment,and reduces the design time of the controller.(2)Design of LQG controller for active suspension without considering the feedback of road input signalsAs the road conditions are completely unknown in the design of a suspension controller,an improved LQG controller is proposed for active suspension system without considering road input signals.The simulation results illustrate that the proposed LQG controller can optimize the comprehensive performance of vehicle suspension system and improve riding comfort and handling safety,which verifies the effectiveness and feasibility of the method.(3)Experimental study on mechanical properties of magnetorheological damperBased on the mechanical properties of the damper,the dynamical characteristics and velocity characteristics of the magnetorheological damper can be obtained.On this basis,the adaptive non-parametric model of the magnetorheological damper is established.The curve by simulation results and the experimental data are the same which can verify the correctness of the model.(4)Design of LQG controller for magnetorheological semi-active suspension systemIn this part,the mechanical model of the magnetorheological damper is applied to the semi-active suspension.The simulation results show that the LQG controller for the magnetorheological semi-active suspension system can achieve almost the same control effect with the active suspension.Because of its simple structure,low energy consumption,the semi-active suspension is worth popularizing.