A switched dynamical system approach towards the optimal control of chemical processes based on a gradient-based parallel optimization algorithm. (4th October 2018) - Wu, Xiang; Lin, Jinxing; Zhang, Kanjian; Cheng, Ming
Highlights: A novel piecewise state feedback controller is introduced. The chemical process optimal control problem is formulated as an optimal control problem of switched dynamical systems. A gradient-based parallel optimization algorithm is developed for solving the optimal control. Convergence results indicate that the gradient-based parallel optimization algorithm is global convergent. Three chemical process optimal control problems are given to illustrate the effectiveness of the proposed algorithm. Abstract: This paper considers an optimal control problem of chemical processes with a novel piecewise state-feedback controller. Firstly, the chemical process optimal control problem is formulated as a switched dynamical system optimal control problem, which can be transformed into a parameter optimization problem. Next, to achieve rapid convergence from remote starting points, we propose a novel gradient-based optimization algorithm, which is suitable to a parallel implementation because the step is improved by updating its direction as well as its length simultaneously before moving to the next iteration, and the step computation involves only the inner products of vectors. Then, the convergent properties of the parameter optimization problem to the original optimal control problem are discussed. Finally, the numerical simulation results show that the gradient-based parallel optimization algorithm is an effective alternative method for solving the chemical process optimal control problems.