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For discrete-time system, Based on an improved SVM of particle swarm algorithm, a new support vector machine sliding mode control theory is proposed. Through SVM parameters identified model and PSO optimization process, reaching law parameter tends to ideal sliding movement is obtained, ensure that optimization with short processing time and high accuracy. Adjust sliding reaching law parameter online by adopting particle swarm optimization and support vector machine, which can overcome the shortage of reaching law parameter required pre-set in the conventional sliding mode control, accelerate the tracking speed, weaken the system chattering, improve quality control. The results show that the method can overcome the shortcomings and deficiencies of optimization parameter optimization’s difficult to find or too long, etc caused by improper handling in the PSO optimization process, and also can solve shortage of the SVM with low accuracy and large computation, which is feasible and effective, with good usability.