Nonlinear control allocation using hybrid optimization algorithm

A nonlinear control allocation scheme is developed using hybrid optimization algorithm. To achieve nonlinear control allocation results, a hybrid optimization algorithm is presented in which the ant colony algorithm and differential evolution algorithm are employed. The nonlinear control allocation problem is divided into two optimal problems which are selecting optimal truncation point combination problem and optimizing the corresponding section coefficients problem. Under this case, the actuators constraints are segmented into some intervals according to the rate limits and position boundary of actuators. The optimal combination of cutoff interval is given through ant colony algorithm searching, and the optimal combination of truncation points is obtained. On the basis of the optimal truncation points, the corresponding truncation point coefficients are optimized by using the differential evolution algorithm. Then, the actuator commands are obtained by the calculation results of truncation points and corresponding truncation point coefficients. Simulation results show that the developed control allocation method is effective and the control requirement can be achieved.