关键词: 鱼群算法, 最小二乘支持向量回归机, 线控转向, 容错控制

Abstract: In view of the disadvantage of the susceptible observer in current fault-tolerant control techniques, this paper presents the Least Squares Support Vector Regression（LS-SVR） based on fish-swarm algorithm to replace the traditional observer. In this approach, the fish-swarm algorithm is utilized to solve the matrix equation in the LS-SVR by iteration, thus, solving the inverse matrix is avoided, so the training time of the LS-SVR is reduced when the optimal solution is obtained. The LS-SVR is utilized to estimate the side-slip angle in the fault-tolerant control. The redundant information of the side-slip angle is contained in the well trained LS-SVR. It can replace the observer to output the estimate value. The simulation results show that the proposed approach provides a higher convergence speed and anti-interference ability.

Key words: fish-swarm algorithm, Least Squares Support Vector Regression（LS-SVR）, steer-by-wire, fault-tolerant control