Model-Based Online Parameter Optimization

Abstract Changing environmental influences as well as changes in internal parameters of mechatronic systems deteriorate the system performance. A good means to ensure good performance despite these impediments is self-optimizing control. This paper presents a new structure for self-optimizing control systems that forms the basis for combining methods of artificial intelligence with those of “classical” adaptive control theory. In an exemplary simulation on a real-time system, this structure is used to build a self-optimizing pressure-supply system. This realization requires a special optimization algorithm, which constitutes another focus of this paper.