超磁致伸缩执行器串级温度控制策略研究

摘要

In order to implement the full-closed loop temperature control of giant magnetostrictive actuator (GMA), a new schematic that uses cascade control strategy to control the temperature of giant magnetostrictive material (GMM) was presented. Based on the heat balance equation, the heat transferring model was derived, and the concrete scheme of the PID cascade control strategy was constructed. Then genetic algorithm was used for PID parameters optimizing. The simulation results showed that the accommodation time and overshoot indices gained by genetic algorithm is better than those gained by simple method. Using the parameters gained by genetic algorithm, the GMA temperature control system was experimented. The accommodation time is 513. 2s and the overshoot is 2. 75% , which suggested that the performance was far better than single-loop control.%为减少温度对超磁致伸缩执行器(GMA)输出位移的影响,采用串级PID控制策略对GMA进行精确温度全闭环控制.通过热平衡方程推导了GMA的传热学数学模型,并建立了串级PID控制策略的实施方案.采用遗传算法对串级PID控制器进行PID参数优化整定.仿真结果表明,遗传算法优化得到的GMM温度阶跃响应曲线的调节时间和超调量指标均优于单纯形法优化后的响应曲线指标.而在GMA温控平台上的试验结果表明,串级PID控制获得的GMM温度阶跃响应调节时间513.2s,超调量2.75％,温控精度可达±0.1℃,控制效果远远优于单环控制.