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Online identification of nonlinear systems is still an important while difficult task in practice. A general and simple online identification method, by delayed cellular neural networks, is proposed for multi-input-multi-output (MIMO) nonlinear systems. The online identification framework is first formulated by delayed cellular neural networks, and the weights of the neural network are updated by...
Gaussian-Hopfield neural network algorithm (GHNNs) is the most commonly used method of solving the identification problem of nonlinear systems, but learning rule (LMS rule) is easy to fall into local optimum. Genetic algorithm (GA) has globally optimal ability and can solve the locally optimal problem well. This paper puts forward GA-GHNNs algorithm and uses GA algorithm to solve the optimum parameters...
Considering the difficulty of large time-delay process control, take advantage of the approaching ability of neural network to nonlinear system, a smith predictor with neural network is constructed. At the same time, use identification-free adaptive algorithm to adjust the coefficient of the single-neuron PSD controller. Combine them, a new control method appear. The result of the simulation indicated...
To realize the adaptive control in the heat tunnel system of fire detector, an adaptive PID control algorithm based on BP network and immune genetic algorithm (IGA) is presented. Firstly, the immune genetic algorithm is used to optimize the weights of BP network, which reduces the influence of control effect due to initial network weights; secondly, the PID parameters are adjusted on line based on...
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