基于粒子群算法的高温高压三轴试验机控制系统优化

Optimization of High-temperature and High-pressure Triaxial Testing Machine Control System Based on Particle Swarm Algorithm

通过将粒子群算法(PSO)与常规PID结合,对高温高压三轴试验机的液压与温控系统进行分析研究,分别建立液压系统和温控系统的数学模型,对比分析了传统PID控制、模糊PID控制和粒子群算法优化PID控制下的控制系统性能。通过Simulink仿真结果表明,与传统PID控制和模糊PID控制相比,粒子群算法优化PID控制可使被控对象很快地收敛于稳态,试验机温度与液压控制系统响应速度快,稳态误差小,超调量小。因此,基于粒子群算法优化PID控制策略对试验机控制系统有较好的效果,能更好满足岩石特性分析。

By combining particle swarm algorithm(PSO)with conventional PID,the hydraulic and temperature control systems of high-temperature and high-pressure triaxial testing machine was analyzed and studied,the mathematical models of hydraulic system and temperature control system were established.The performance of the control system under conventional PID control,fuzzy PID control,and particle swarm algorithm optimized PID control was compared and analyzed.The Simulink simulation results show that compared with traditional PID control and fuzzy PID control,the particle swarm algorithm optimized PID control can make the controlled object converge to steady state quickly,and the temperature and hydraulic control systems of the testing machine respond quickly,with small steady state error and small overshoot.Therefore,the optimized PID control strategy based on the particle swarm algorithm for testing machine control system has a better effect,and can better meet rock characteristics analysis.