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- 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
ab
- 基于遗传算法和基于粒子群算法的改进近似模型,对比图象和理论-Based on Genetic Algorithm and Particle Swarm Optimization Based on Improved approximation model, image contrast and theoretical
svm_v251
- 遗传算法和粒子群算法优化的近似模型,图象,理论与对比等说明。-Approximate model of genetic algorithm and particle swarm optimization, the image, and contrast theory and explanation.
pso
- 粒子群算法是目前人工智能的基础算法,本程序是初学者更好的学习遗传算法的基础-Particle swarm algorithm is the basic algorithm of artificial intelligence. This procedure is the basis of the better learning genetic algorithm for beginners.