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 ...

  The optimal harvesting policy is calculated as a function of the entering stock, the price state, the harvesting cost, and the rate of interest in the capital market. In order to determine the optimal harvest schedule, the growth function and stumpage price process are estimated for the Swedish mixed species forests. The stumpage price is assumed to follow a stochastic Markov process. A stoch...

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

A neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem which is implemented with adaptive critic neural network. The proposed simulation method is illustrated by the optimal control problem of nitrogen transformation cycle model. Results...

this paper deals with optimal operation of a three-product dividing-wall column (dwc). the main idea is to design a control structure, through a systematic procedure for plantwide control, with an objective to achieve desired product purities with the minimum use of energy. exact local method is used to find the best controlled variables as single measurement or combination of measurements base...

this paper presents a theoretical approach to implementation of the “multi-realization of nonlinear mimo systems”. this method aims to find state-variable realization for a set of systems, sharing as many parameters as possible. in this paper a special nonlinear multi-realization problem, namely the multi-realization of feedback linearizable nonlinear systems is considered and an algorithm for ...

this paper presents a discrete-time robust control for electrically driven robot manipulators in the task space. a novel discrete-time model-free control law is proposed by employing an adaptive fuzzy estimator for the compensation of the uncertainty including model uncertainty, external disturbances and discretization error. parameters of the fuzzy estimator are adapted to minimize the estimat...