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Aiming at the characteristics such as multivariable, strong coupling, nonlinear and time-varying parameters for the coordinated control system of unit power plant, a single-nerve cell network combined with PID control method was presented. A modified mutative scale chaotic optimization algorithm was proposed for the use of tuning the weight parameters of neural network and PID parameters. The new...
Based on the electromagnetism-like algorithm (EM), we propose a novel hybrid learning algorithms which is the improved EM algorithm with back-propagation technique (IEMBP) for recurrent fuzzy neural system design. IEMBP are composed of initialization, local search, total force calculation, movement, and evaluation. They are hybridization of EM and BP. EM algorithm is a population-based meta-heuristic...
An improved PID neural network-based controller is designed and analyzed for the inverted pendulum system. In order to deal with the local minimum problem in training neural network with backpropagation algorithm and to enhance controlling precision, neural network's weights are adjusted by optimization algorithm. The controller employs a PID neural network instead of estimating the unknown plant...
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