Nonlinear model predictive control based on lexicographic multi-objective genetic algorithm

By using a series of dynamic coefficients in fitness function, a modified genetic algorithm is proposed. It can solve the lexicographic multi-objective optimization problem stemmed from multivariable nonlinear model predictive control directly. A control problem of a two-tank control system is then given as an example. Stair-like control strategy and feedback compensation are also used to develop a better performance of the controller. Simulation results verify the efficiency of the algorithm.