Four-wheel steering model prediction control method based on data driving

Abstract

The invention belongs to the technical field of four-wheel steering control, and discloses a four-wheel steering model prediction control method based on data driving. The method comprises the following steps of: establishing a reference model, namely establishing the reference model by considering the stability factor of a vehicle and road adhesion conditions, and determining an expected side slip angle [beta]* and yaw velocity [gamma]* according to the reference model; designing a nonlinear model prediction controller, namely, designing the nonlinear model prediction controller considering constraints in combination with a map-based two-degree-of-freedom model, and inputting the expected side slip angle [beta]* and yaw velocity [gamma]* into a nonlinear controller module; and according to the expected side slip angle [beta]* and yaw velocity [gamma]* and the actual side slip angle beta and yaw velocity gamma which are fed back in real time and output by the vehicle system, optimizingand calculating front and rear wheel rotation angles of the vehicle, and outputting the optimized front and rear wheel rotation angles of the vehicle to the vehicle system. In conclusion, the methodhas the advantages of being high in stability, small in calculation burden and high in safety.

Description

technical field [0001] The invention belongs to the technical field of four-wheel steering control, in particular to a data-driven four-wheel steering model predictive control method. Background technique [0002] The control-by-wire active four-wheel steering technology is a comprehensive chassis technology that can effectively improve vehicle handling stability, driving comfort, and active safety. Development direction, with good commercial value and development prospects. [0003] At present, the control methods and controllers for controlling the stability of four-wheel steering mainly include the following: [0004] 1) if figure 1 As shown in , assuming that the tire slip angle is between [-0.1,0.1], a linear model is established, and the controller is designed according to the linear model; however, the controller ignores the working condition that the tire characteristics are in the nonlinear interval, once the vehicle is in In extreme working conditions, the side ...

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Problems solved by technology

[0004] 1) if figure 1 As shown in , assuming that the tire slip angle is between [-0.1,0.1], a linear model is established, and the controller is designed according to the linear model; however, the controller ignores the working condition that the tire characteristics are in the nonlinear interval, once the vehicle is in In extreme working conditions, the side slip angle of the tire will be in the nonlinear region, and the linear controller will lose its function at this time, and the stability of the controlled object cannot be guaranteed.

[0005] 2) Fit the nonlinear characteristics of tires through magic formulas, neural networks, etc., establish a nonlinear mechanism model, and design a controller based on the mechanism model; however, the controller has the problems of long calculation time, large amount of calculation, and difficult implementation

[0006] 3) Determine the relationship between the front and rear wheel angles through multiple simulation experiments with different speeds and different front wheel angle inputs, establish fuzzy logic and fuzzy control methods based on this relationship, and design four-wheel steering vehicles based on the fuzzy control method controller; however, the fuzzy logic in the controller is obtained based on real vehicle simulation experiments, which has certain limitations, and it is difficult to achieve universal application for all vehicles

[0007] 4) Other methods, such as sliding mode control, LQR control, etc., but none of them can deal with actuator constraints, such as front and rear wheel rotation angle constraints

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