共查询到15条相似文献,搜索用时 56 毫秒
1.
2.
3.
4.
针对一般滑模控制中存在的系统抖振问题,提出了一种基于模糊遗传算法的滑模变结构控制无刷直流电动机方法.通过使用遗传算法优化的模糊控制柔化滑模控制输出,有效地减小系统抖振.该方法能使系统较好地实现输入参考模型的跟踪,具有自适应强、鲁棒性好的特点. 相似文献
5.
基于改进BP神经网络PID的无刷直流电动机速度控制的研究 总被引:1,自引:0,他引:1
引进模糊归一化控制策略,在线实时地调整与收敛速度密切相关的学习速率和动量系数,克服了BP网络收敛慢和容易陷入局部最小的缺点,并将改进的BP神经网络PID算法成功应用于无刷直流电动机速度控制中。仿真结果表明,改进BP神经网络PID使收敛变得更快,而且系统具有较强的鲁棒性和自适应能力。 相似文献
6.
7.
8.
9.
无刷直流电动机调速系统的模糊变结构控制 总被引:2,自引:1,他引:2
分析了无刷直流电动机数学模型,提出了将模糊控制与PI控制相结合的变结构控制新方法。当输入偏差大于或小于设定值时,采用模糊结构或PI结构进行控制。仿真结果表明该方法较传统PI控制具有更好的动、静态特性,并有较高的精度和鲁棒性。 相似文献
10.
11.
Kamaraj Premkumar Bairavan Veerayan Manikandan Chellappan Agees Kumar 《电力部件与系统》2017,45(20):2304-2317
In this paper, Antlion algorithm optimized Fuzzy PID supervised on-line Recurrent Fuzzy Neural Network based controller is proposed for the speed control of Brushless DC motor. Learning parameters of the supervised on-line recurrent fuzzy neural network controller, i.e., learning rate (η), dynamic factor (α), and number nodes (Ni) are optimized using Genetic algorithm, Particle Swarm optimization, Ant colony optimization, Bat algorithm, and Antlion algorithm. The proposed controller is tested with different operating conditions of the Brushless DC motor, such as varying load conditions and varying set speed conditions. The time domain specifications such as rise time, overshoot, undershoot, settling time, recovery time, and steady state error and also integral performance indices such as root mean square error, integral of absolute error, integral of squared error, and integral of time multiplied absolute error are measured and compared for above optimized controller. Simulation results show Antlion algorithm optimized Fuzzy PID supervised on-line recurrent fuzzy neural network based controller has proved to be superior than other considered controllers in all aspects. In addition, the experimental verification of proposed control system is presented to test the effectiveness of the proposed controller with different operating conditions of the Brushless DC motor. 相似文献
12.
13.
14.
15.
针对多变量、非线性、时变的永磁无刷直流电机位置伺服控制系统的特点,提出一种基于免疫遗传算法(IGA)的递归模糊神经网络(RFNN)控制器的设计方法,并应用于无刷直流电机三闭环控制系统中的位置调节器中,实现系统精确的位置控制。在与传统PID位置控制器仿真比较中,采用该方法的系统显示出良好的控制性能和控制效果。 相似文献