煤矿局部通风机转速控制算法研究

Research on speed control algorithm of coal mine local ventilator

煤矿局部通风机系统目前主要采用常规PID控制算法进行变频调速,但PID控制参数的调整主要依赖人工经验,调节时间长、实时性差,且容易发生控制量超调和振荡输出。针对上述问题,提出了一种粒子群(PSO)优化PID控制算法,并将其应用到煤矿局部通风机转速控制中,即在基于常规PID控制算法的煤矿局部通风机转速控制系统中添加PSO算法,实现PID控制参数优化。常规PID控制部分直接按照Z-N整定法得出的最优参数设置运行;PSO优化PID控制部分通过S函数算法程序随机产生一组三维粒子,通过调用函数assignin将三维粒子的值赋给转速控制系统仿真模型中的Kp,Ki,Kd三个参数,以控制系统误差指标ITAE作为适应度函数进行迭代寻优,实现了PSO寻优与PID参数整定优化的统一。仿真实验结果表明,相比于常规PID控制,经过PSO算法优化后,局部通风机转速控制输出性能改善明显,尤其是超调量和调节时间指标,超调量仅为常规PID控制算法的20%。

At present,coal mine local ventilator system mainly adopts conventional PID control algorithm to carry out frequency-conversion speed-regulation,but the conventional PID control parameter adjustment mainly relies on artificial experience,adjustment time is long,real time is poor,and easy to occur over-regulating and oscillating output of the control quantity.To solve the above problems,a particle swarm optimization(PSO)optimized PID control algorithm was proposed and applied to the speed control of coal mine local ventilator.PSO algorithm is added to the speed control system of coal mine local ventilator based on the conventional PID control algorithm to realize PID control parameter optimization.The conventional PID control part directly runs in accordance with the optimal parameter setting obtained by Z-N tuning method;PSO optimized PID control part randomly generated a set of three-dimensional particles through the algorithm program of S function,and calls the function assignin to assign three-dimensional particles values to Kp,Ki,Kd parameters of speed control system simulation model,taking control system error indicator ITAE as fitness function for iterative optimization,unity of PSO optimization and PID parameter setting optimization is realized.The simulation results show that compared with the conventional PID control,after PSO algorithm optimization,the output performance of local ventilator speed control are improved significantly,especially the overshoot and the regulation time index,and the overshoot is only 20%of the conventional PID control algorithm.