Study On Intelligent Optimal Sliding Mode Control Of Semi-active Suspension

The vehicle suspension system is the "link" that connects the ground and the frame.It not only affects the grounding of the tires and thus the driving safety of the vehicle,but also can attenuate the vertical vibrations caused by uneven ground,optimize the smoothness of the vehicle.Semi-active suspension changes the damping characteristics of the damper according to the suspension system’s state to adapt to different vehicle driving conditions.Compared to active suspension,semi-active suspension is widely favored in the market due to its advantages of low energy consumption and low cost.However,it has strong nonlinear mechanical characteristics that must be overcome when designing semi-active suspension controllers.This paper chooses solenoid valve dampers as the research object.Although it has more complex nonlinear characteristics,it is more reliable and cost-effective.The paper proposes a new method of establishing a damper model using neural networks,specifically addressing its more complex nonlinear characteristics.In addition,to solve the nonlinear and robustness problems of the semi-active suspension system,this paper chooses the sliding mode control strategy for continuous damping control and optimizes its parameters using genetic algorithms and improved particle swarm optimization.The experimental results show significant improvement in the overall control effect of the suspension.Furthermore,this paper establishes a fuzzy coordinated controller to compensate for vehicle attitude control,and verifies the feasibility of the coordinated controller and sliding mode controller in the half-car suspension system through simulation.In summary,this research that provides a new method and ideas for semi-active suspension control,is of great significance in the field of semi-active suspension control.The main content of this paper is as follows:(1)Establish a suspension dynamics model and road excitation model.Conduct dynamic experiments on a certain passenger car’s Solenoid valve damper at different current levels using an MTS shock absorber characteristic test bench and collect experimental data.Use an optimized neural network to learn from the experimental data and establish a solenoid valve damper model based on the experimental data.Consider the neural network shock absorber model in the vehicle suspension,and consider the motion conditions of the semi-active suspension,set "boundary conditions" and establish two suspension models and convex block road and random road excitation models based on Simulink.(2)Establish a GA-UPSO(Genetic Algorithm-improved Particle Swarm Optimization)optimized sliding mode controller and conduct simulation analysis.Establish a sliding mode controller with the ideal ceiling-floor model as the reference model.Use particle swarm algorithm to optimize the mix-shedding ratio coefficient and sliding mode approach law parameters with the suspension comprehensive performance as the objective function.To overcome the disadvantage of particle swarm algorithm easily falling into a local optimal solution,use a combination of genetic algorithm and improved particle swarm algorithm.Simulate under different road conditions,and analyze that the control effect of different control strategies.(3)Build a vehicle attitude coordination controller and verify it through simulation.Based on the GA-UPSO optimized sliding mode controller,establish a coordination controller.Obtain the vehicle attitude control strategy based on fuzzy control algorithm,and then allocate it to the front and rear shock absorbers through compensation strategy to control the vehicle pitch angle.Simulate through Simulink and verify the effectiveness of the vehicle attitude coordination controller in suppressing vehicle pitch vibration.(4)Verify the GA-UPSO optimized sliding mode control strategy through bench tests.Build a 1/4 scaled suspension test bench for the vehicle,including suspension system,actuator,sensor,and control system.Through comparative tests,the GA-UPSO optimized sliding mode controller proposed in this paper can optimize the suspension comfort while ensuring the safety of the vehicle.