| Complex large-scale systems such as unmanned aerial vehicles are required to behave in an autonomous manner under uncertain environmental conditions. Typically, these systems are required to operate in a finite number of operational modes that necessitate robust, stable and smooth transitions between them. In this thesis, mode transition control algorithms are developed for the following three problems: (1) transitioning from a start mode to a goal mode of operation; (2) transitioning from a family of start modes to a family of similar goal modes; (3) assessing the performance of mode transition controllers designed to transition a system from a start mode of operation to a goal mode. A systematic procedure is developed for the off-line design of mode transition controllers via the method of blending local mode controllers. And, an online adaptation scheme is developed for adapting the off-line designed mode transition controller's parameters such that a desired transition trajectory is tracked. Instead of designing and implementing mode transition controllers for all possible combination of transitions between the two family of modes, an intelligent technique is developed to design controllers online real-time, as they are needed, by blending knowledge from a small set of existing mode transition controllers between the two family of modes. Also, a performance assessment tool is developed to measure the robustness of mode transition controllers with respect to initial condition uncertainty or parametric changes of the system to be controlled. Finally, the software implementation of the off-line designed mode transition controllers and the online adaptation scheme is discussed. The developed mode transition control algorithms are illustrated via a series of simulation for a hover to forward flight mode transition control of a helicopter encountering parametric changes and wind disturbances. |
