Abstract— In this paper, a computational method for solving constrained nonlinear optimal control problems is presented with an application to the container crane. The method is based on Banks' et al. iterative approach, in which the nonlinear system state equations are replaced by a sequence of time-varying linear systems. Therefore, The constrained nonlinear optimal control problem can be con...

This paper presents a constrained adaptive dynamic programming (CADP) algorithm to solve general nonlinear nonaffine optimal control problems with known dynamics. Unlike previous ADP algorithms, it can directly deal state constraints. Firstly, generalized policy iteration (CGPI) framework is developed handle constraints by transforming the traditional improvement process into optimization probl...

This paper deals with the optimal control problem for a class of affine nonlinear discrete-time systems. By introducing a sensitivity parameter and expanding the system variables into a Maclaurin series around it, we transform the original optimal control problem for affine nonlinear discrete-time systems into the optimal control problem for a sequence of linear discretetime systems. The optima...

To solving nonlinear control problems and especially nonlinear optimal control problems (NOCP), classical methods are not usually efficient. In this paper we introduce a new approach for solving this class of problems by using Nonlinear Programming Problem (NLPP). First, we transfer the original problem to a new problem in form of calculus of variations. Then we discretize the new problem and s...

OF THE DISSERTATION Self-Organizing and Optimal Control for Nonlinear Systems by Wenjie Dong Doctor of Philosophy, Graduate Program in Electrical Engineering University of California, Riverside, June 2009 Professor Jay A. Farrell, Chairperson Vehicle formation control is one of important research topics in transportation. Control of uncertain nonlinear systems is one of fundamental problems in ...

This paper addresses the real-time optimal control of a Pendubot using nonlinear model predictive control (NMPC) combined with nonlinear moving horizon estimation (MHE). This fast, under-actuated nonlinear mechatronic system apparently poses a challenging benchmark problem that may benefit from a nonlinear optimization scheme. To overcome the related computational difficulties we make use of th...