The simplification of neural network for quadratic programming problems and its applications in optimal control

In this paper, a kind of neural network for quadratic programming problems is first simplified. The simplification is necessary for high accuracy solutions and low cost implementation; the simplified model has high performance. The proposed neural network is used to solve quadratic control problems for discrete linear systems with constraints. The simulation proved the rationality of the results obtained.