PID控制器的性能取决于其控制参数的组合，针对其参数的整定和优化问题，提出了应用一种改进的粒子群优化算法，该 算法借鉴了遗传算法的杂交机制，并采用惯性权值的非线性递减策略。用以加速算法的收敛速度和提高粒子的搜索能力。将该算 法应用于一个二阶系统的PID控制器参数的优化。仿真结果表明该改进的粒子群算法具有比传统粒子群算法和遗传算法更好的 优化效果，具有一定的工程应用前景。-Abstract：PID controller’s performance completely depends

Abstract A particle swarm optimization method with nonlinear time-varying evolution (PSO-NTVE) is employed in designing an optimal PID controller for asymptotic stabilization of a pendubot system. In the PSO-NTVE method, parameters are determ

This paper presents a method for optimum tuning of Fractional PID controllers using PSO algorithm which have fractional or integer order transfer functions. Particle swarm optimization (PSO) is a robust stochastic optimization technique based on the