Optimal control of distillation column using Non-Dominated Sorting Genetic Algorithm-II

Many control problems involve simultaneous optimization of multiple performance measures that are often non-commensurable and competing with each other. The presence of multiple objectives in a problem usually gives rise to one set of optimal solutions, largely known as Pareto-optimal solutions. In this paper, the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) has been successfully applied to optimization of dynamic state of simple distillation process. This paper presents the tuning of Proportional-Integral-Derivative (PID) controllers by minimizing of three objective functions (overshoot, response time, and Integral of Absolute Error (IAE)) through NSGA-II. A MATLAB code for real-parameter NSGA-II has been coupled with HYSYS v.3.1 process simulator for simulation and optimization of process. Optimization numerical results show that genetic algorithm is more suitable method for optimal control of distillation columns than traditional methods.