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液压推进系统在硬岩掘进机(Tunnel Boring Machine,TBM)掘进过程中起重要作用,其控制性能直接影响掘进的安全与效率。采用传统的试凑法对TBM推进系统PID控制参数进行人工调整,不仅工作量大且难以达到较好的控制效果。分析TBM液压推进系统机理,建立了液压推进系统模型,提出基于粒子群算法(Particle Swarm Optimization,PSO)的PID控制器参数优化策略。将PID控制器参数当成粒子群中的粒子,得到最优粒子作为液压推进系统PID控制器参数。仿真结果显示,PSO-PID控制器获得了较好的控制性能。
The hydraulic propulsion system plays an important role in tunnel boring machine (TBM) tunneling, and its control performance directly affects the safety and efficiency of tunneling. The traditional trial and error method is adopted to manually adjust the PID control parameters of the TBM propulsion system, which is not only heavy workload but also difficult to achieve better control effect. The mechanism of TBM hydraulic propulsion system is analyzed and a hydraulic propulsion system model is established. A PID controller parameter optimization strategy based on Particle Swarm Optimization (PSO) is proposed. The parameters of the PID controller are regarded as the particles in the particle swarm optimization, and the optimal particle is obtained as the PID controller parameter of the hydraulic propulsion system. Simulation results show that the PSO-PID controller obtains better control performance.