Friction is widely present in moving mechanical systems, and it has a negative impact on the performance of mechanical systems, such as tracking errors during low-speed motion. To overcome the impact of friction on the control accuracy of the system, this paper proposes a dynamic continuous friction model based on numerous current friction models. Based on this friction model, the velocity control mode of the direct-drive system is compensated for, and good results have been achieved.

The sensitivity analysis is investigated to solve multi-objective optimization problems with cell mapping in high-dimensional parameter space. A post-processing algorithm is introduced to help choose control parameters from the Pareto set. An optimal-sliding-mode combined-control strategy is proposed to solve global optimal tracking control problems for a MIMO system. The schemes proposed are applied successfully in the control optimization for an antenna servo system on a disturbed carrier.

Obstacle avoidance and path-tracking control of intelligent vehicles have always been the key issues of intelligent vehicles. This paper improves the traditional model predictive control algorithm. According to the simulation results, compared with the traditional model predictive control, the proposed adaptive model predictive control algorithm can not only avoid obstacles, but also improve the vehicle path-tracking accuracy and driving stability.

The speed of autonomous vehicles will have a significant influence on the safety and comfort of driving. When the autonomous vehicle passes through the consecutive speed control humps, how to automatically select the most appropriate speed has become a practical research subject. The paper chooses the genetic algorithm to build a multi-objective optimization model and then designs and carries out the solution process of the multi-objective optimization problem for the vehicle.

An analytical solution for designing the optimal parameters of dynamic vibration absorbers attached to the damped main system is found to be difficult and complicated. In this paper, the adaptive multiswarm particle swarm optimization is applied to parameter optimization, and the numerical solutions of the system are given for the damped main system under sinusoidal force excitation.