基于路面识别的非线性悬架系统自适应控制

To adjust the control parameters according to road levels and study the characteristics of suspension nonlinear parameters under different road levels, an algorithm was proposed based on cuckoo search optimization and road estimation. Firstly, a quarter nonlinear suspension model with nonlinear dampers and springs was created, which sprung mass acceleration and tire deflection were taken as the optimization objective and the current of nonlinear dampers was taken as the optimization variable. Then, a cuckoo search-based multi-objective optimization method was used to calculate the optimal control parameter, and a road estimation method was used to identify the road level to adaptively adjust the system performance according to road input. The simulation results showed that: 1) the road estimation and cuckoo search-based algorithm can adjust the control parameter adaptively according to road levels, and the proposed method can improve riding comfort when the tire keeps contacting the road surface; 2) compared with the particle swarm optimization (PSO), the current calculated by cuckoo search can provide better suspension performances.