Optimal attitude control parameters via stochastic optimization framework for autonomous aircraft

An attitude control system based on a traditional feedback control with optimized parameters is presented. This system is part of a much larger global control structure designed for autonomous robotic aircraft. The global control structure consists of a high level structure for mission and supervision control, an intermediate structure for navigation and obstacle management, and a low level structure control, which deals with stability and attitude control. Thus is of paramount importance to have a highly efficient low level control since it affects directly the upper levels and ultimately the full aircraft operation. The solution for finding the best control parameters is found by applying a Stochastic Optimization Framework (SOF; Fink, SPIE 2008) to optimize aircraft response for low level commands, which are for the airplane the attitude angles (roll, pitch, and yaw) and the engine throttle. The basic controllers for the attitude are conventional PID controllers for each controlled variable. The SOF optimization procedure tries to find global parameters for these controllers to optimize the global performance index, i.e., to minimize the sum of the squared integration errors of all the controllers. In consequence the optimized parameters significantly improve low level control (attitude regulation and changing).