开发用于高性能电动驱动器的智能控制器,使用混合CSA和RERNN技术
J Prabhakaran1, P Thirumoorthi2, M Mathankumar3
1Department of Electrical and Electronics Engineering, Mahendra Engineering College, Mallasamudram, Namakkal, India. j.prabhakaranresearch@gmail.com.
一个新的混合智能控制器,CSA-RERNN (Circle Search Algorithm-Recalling-Enhanced Recurrent Neural Network) 改进了电动驱动的速度控制. 这种强大的方法确保了工业应用中稳定的性能和成本效益.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 人工智能的人工智能
背景情况:
- 电动驱动器在工业中至关重要,在变化条件下需要精确控制.
- 现有的控制方法面临复杂的机械配置和参数波动的挑战.
研究的目的:
- 开发一种智能控制器,用于精确控制电动驱动器的速度.
- 为了提高不同参数的电动驱动系统的适应性和稳定性.
主要方法:
- 开发了一种混合方法,结合了循环搜索算法 (CSA) 和回忆增强反复神经网络 (RERNN) (CSA-RERNN).
- CSA优化了电压源逆变器控制信号,而RERNN则预测了最佳信号.
- 该系统考虑了诸如惯性,负载扭矩和转子轴角度等变量.
主要成果:
- 在MATLAB/Simulink模拟中,CSA-RERNN在SSA,ANN和BCO上表现出优越的性能.
- 实验结果显示,错误率较低,速度控制精度提高.
- 系统保持了稳定的响应特征,尽管惯性波动 (1.2-2.3 kgm2).
结论:
- CSA-RERNN技术为电动驱动控制提供了强大,稳定和具有成本效益的解决方案.
- 它确保了长期的性能稳定性,而不会使适应机制失效.
- 这种方法适用于需要智能电动驱动控制的各种工业应用.
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