Design and Implementation of intelligent furniture Control System Based on Improved Particle Swarm optimization

The functions of smart home products should be based on the needs of users. Only smart home products that can really solve the pain points of users can be recognized by the market. The emergence of all kinds of smart home devices began to form a new consumption frenzy. This paper studies the design and implementation of intelligent furniture control system based on improved PSO (Particle swarm optimization) algorithm. The topology of intelligent furniture control system is established. In order to improve the system performance, an improved PSO algorithm is proposed to optimize the PID controller parameters. Evolutionary speed factor and aggregation factor are introduced to improve the PSO algorithm. The improved PSO algorithm evaluates whether the particles are the best value by fitness value in the process of searching evolution. Simulation results show that the optimized parameters of improved PSO algorithm have the advantages of fast convergence speed, high convergence precision and strong anti-interference ability. The parameters of PID controller adjusted by improved PSO algorithm have better performance indexes in overshoot, steady-state error, adjustment time and so on.