【摘要】 利用免疫系统的克隆选择原理设计了全局搜索优化算法和局部搜索优化算法,并提出了一种时变对象的模糊控制器参数自整定方案。该方案利用全局优化算法离线组合优化标称参数下的控制器,对象发生变化后,利用局部优化算法在线优化,可快速获得新的控制器参数,以实现自适应控制。仿真结果表明,该控制系统在被控对象参数变化的情况下,仍具有良好的控制性能,能够对一类时变对象实施高精度控制,具有较大的工程应用价值。更多还原

【Abstract】 A global and a local optimization algorithms are designed by imitating clone selection process in immune system, and then an effective self-tuning scheme of fuzzy controller is proposed for time-variable plant. For a time-variable plant, the global optimization algorithm is adopted to optimize nominal controller offline. By using local optimization, new optimized controller can be rapidly obtained near the nominal controller when the plant changes. New controller can be switched to implement selftuning control and improve the performance. Simulations show that the system has strong robustness and can implement high accuracy control for some industrial plants.更多还原