Pareto optimum design of an adaptive robust backstepping controller for an unmanned aerial vehicle

This research develops an adaptive robust backstepping (AR-backstepping) controller for stabilization of an unmanned aerial vehicle (UAV) having strong coupling and highly nonlinear dynamics. At first, the backstepping control method as the basic stabilizer is utilized to determine the control efforts of the considered UAV. Next, an adaptive-robust mechanism subject to gradient decent methods and sliding surfaces is implemented to regulate the control gains. In fact, this mechanism determines the speed of changes of the gain values of the backstepping controller to make better responses in the presence of disturbances and uncertainties. Then, the optimum values of the design parameters related to the adaptive-robust mechanism are selected by using a multi-objective ant-lion optimization (MOALO) algorithm to simultaneously minimize the total error and control efforts. Finally, the results for a UAV developed in the Sirjan University of Technology, Sirjan, Iran, are given to confirm the effectiveness, robustness, and advantages of the designed AR-backstepping controller.