Research On Accurate Position Control Of AMT Selecting And Shifting Actuator Based On Model-free Adaptive Theory

As a key part of the vehicle powertrain,the transmission has a decisive influence on the power transmission in vehicle.Automated Mechanical Transmission(AMT)has always been favored due to its high power transmission efficiency and low cost.However,the long-term interruption of AMT during gear shifting seriously affects the driveability,dynamics and comfort of the vehicle.In this paper,a certain type of five-speed AMT is used as the research carrier,and the electronically controlled electric selecting and shifting actuator as the research object.In order to achieve the precise position control,reduce the shift interruption time and shift impact,the selecting and shifting actuator be made the following research:(1)First of all,analysis and modeling of the selecting and shifting actuator.According to the execution mechanism of the actuator in the AMT shift control system,a mathematical model of the actuator’s power source-the brushed DC motor and other mechanical structure is built,and the motor model parameters are identified.(2)Next,design of the position controller for the selecting and shifting actuator.A novel propotion model-free adaptive cascade controller(P-MFAC)is designed to realize the precise position control of the AMT selecting and shifting actuator.The controller consists of a speed inner loop controlled by model-free adaptive control(MFAC)and a position outer loop controlled by a proportional link.The simulation results show that,compared with the traditional PID controller and the sliding mode robust controller based on the reaching law,the P-MFAC controller performs well in fast and accurate position tracking control,without large overshoot and steady state error.(3)Afterwards,P-MFAC controller parameter tunning.Aiming at the problem that the P-MFAC controller mainly relies on experience for parameter tuning and it is difficult to obtain the optimal solution by manual tuning,the basic particle swarm algorithm and artificial immune algorithm are combined to form an immune particle swarm algorithm,and the controller parameters are optimized to make the controller reach optimal position control effect.The simulation results show that the algorithm has faster convergence speed,stronger global search ability,and higher convergence accuracy and stability,compared with genetic algorithm and particle swarm algorithm.(4)Eventually,bench test verification.First,completing the precise position control of a single target gear to verify the effectiveness and superiority of the P-MFAC control algorithm.Then many static switching tests to all gears are carried out,and the reliability and advancement of the controller proposed in this paper are verified by comparing the shift durations with the traditional PID controller.