Constrained optimal control problems of nonlinear systems based on improved Newton algorithms
In this paper, we consider an optimal control problem of constrained nonlinear systems. By standard optimization methods, it is difficult to solve the problem, since such constraints are very complex. To overcome this difficulty, by a smoothing technique and a penalty function method, an improved Newton algorithm is developed for solving the problem. Convergence results indicate that the proposed methods is globally convergent with quadratic rate. Finally, numerical results indicate that our method is effective compared to existing methods.
2016 3rd International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)