粒子群优化模糊PID的塔式起重机定位和防摆研究

针对塔式起重机控制系统是一个大时滞性、时变及非线性的控制系统,无法建立准确数学模型,难以进行精确控制的问题,设计了模糊PID控制器,通过模糊推理对PID的参数进行在线调整,但由于专家经验具有局限性、盲目性以及模糊控制内不确定因子过多,导致控制性能较差。因此,本文采用粒子群算法对量化因子和比例因子先在离线状态下进行迭代优化后,快速整定模糊PID参数,然后通过MATLAB对控制系统进行仿真分析。仿真结果表明,该方法明显提升了负载的运输效率,有效抑制了塔式起重机负载摆角,并实现了塔式起重机快速准确定位,具有较强的鲁棒性。

Study on Positioning and Anti-pendulum of Tower Crane Based on Particle Swarm Optimization Fuzzy PID

For tower crane control system is a big time lag, time-varying and nonlinear control system, unable to establish accurate mathematical model, it is difficult to accurately control the problem of the fuzzy PID controller is designed, through fuzzy inference to adjust PID parameters on-line, but because the expert experience has limitations, blindness, and fuzzy control of excessive uncertain factors leading to poor control performance. Therefore, in this paper, particle swarm optimization is adopted for the iterative optimization of quantization factor and scaling factor under the off-line state first, then the fuzzy PID parameters are quickly adjusted, and then the control system is simulated and analyzed by MATLAB. The simulation results show that this method can reduce the load swing Angle of the tower crane obviously, and realize the fast and accurate positioning of the tower crane with good robustness.