Stable-state optimal control for pulp washing process

In order to solve the multi-objective optimal control of pulp washing process with long time delay, a new method is proposed in this paper. Pulp washing process optimization problem is often be described as a nonlinear constrained problem. By introducing adaptive penalty factor, the nonlinear constrained problem can be converted to an unconstrained problem. Then a stable model of pulp washing is established. Based on the stable model and the exact parameters obtained by neural network, chaotic optimization algorithm is used for the multi-objective optimization. Empirical results show that after optimization, each of the indices meet the requirement and maintain a more stable value. The method is feasible in solving the optimal control of pulp washing process, it can bring greater economic benefits to pulp and paper enterprises.