Motion Control of Inspection Robot Based on Membrane Calculation Particle Swarm Algorithm
In response to the problem of low efficiency and difficult stability of mining inspection robots in the working process.A PID parameter self-tuning controller based on membrane computing optimization particle swarm optimization algorithm was designed.Firstly,according to the uneven road surface in the mining area and the characteristics of the robot itself,its motion model was established.Second,a single-layer membrane structure model is used to optimize the particle swarm optimization design,resulting in the membrane computing optimization particle swarm optimization(MC-PSO)algorithm.The three control parameters of PID are encoded as the objects optimized by the MC-PSO algorithm,obtaining ideal optimal values through empathy,communication,cross and rewrite.Finally,simulation experiments were conducted and compared with traditional PID and Fuzzy PID.The experimental data showed that the average system error was reduced by 0.23 m and 0.16m,and the system adjustment time was reduced by 4.6 s and 3.08 s,which veri-fied that this algorithm has good effects in improving system response speed,control accuracy,and robustness.
万方数据
维普
