Research Of Hopfield Network And Its Application In Power Plant

Hopfield network is one kind of recurrent neural network. All of its neurons are connected to each other and it has rich dynamic characteristics. Hopfield network has been applied to optimal computation and associative memory and proved to be very effective. But the network has some defects such as converging to local minimum. Its research and application in control is also in an initial stage, and its application in power plant is blank. This paper proposes some improvements of Hopfield network and makes thorough research on its application in power plant: predictive control based on Hopfield network applied in main steam pressure system and unit load system; the identification and control of single infinite big system; economic dispatch problem solving by Hopfield network. These researches expand the application area of Hopfield network and get rich achievements.In order to overcome the defects of Hopfield network, this paper proposes the method of adaptive step size to accelerate the network's convergence. Combinine the augmented Lagrange method with Hopfield network to improve the quality of solutions. Introduce the simulated annealing and chaos into Hopfield network in order to help the network to escape the local minimum. By experiments and comparisons, these improvements are very effective.Predictive control is one kind of optimal control. This paper analyzes Model Algorithm Control (MAC) and General Predictive Control (GPC), then converts them into typical quadratic optimal problems with constraints and construct Hopfield network to get the future control series. These new methods are applied to control the main steam pressure system and unit load system, the former is a SISO plant and the later is MIMO plant. Simulations prove the good results.Hopfield network is an affine nonlinear system. After proper training, it can identify the affine nonliear system. After theoretical analysis, Hopfield network combining with nonliear state feedback linearization method is used to control the single infinite big system and gets good control performance. This paper also discusses the control of boiler-turbine system, which is a MIMO plant.Economic dispatch problem is an optimal problem. Proper economic dispatch can bring great economic benefits. This paper proposes the double Hopfield network, one network is used to minimize the cost function, and the other is used to satisfy the constraints. They are independent each other. Two examples prove the good effect. This paper also discusses the application of Hopfield network in TSP problem. After analyzing the dynamic characteristic of network, some modifications are proposed to improve the network's performance. This paper also makes initial research in model reference adaptive control.Hopfield network has rich dynamic characteristic and promising applications. After summarization, this paper proposes the areas on which research should focus.