Modeling estimation and identification of complex system dynamics. Issues and solutions

      Аннотация: Models of real systems are of fundamental importance in virtually all disciplines. Models can be useful for system analysis, i.e. for gaining a better understanding of the system. Models make it possible to predict or simulate a system's behavior. In engineering, models are required for the design of new processes and for the analysis of existing processes. Advanced techniques for the design of controllers, optimization, supervision, fault detection and diagnosis components are also based on models of processes. Modeling and identification of systems are of fundamental importance, and the quality of the model typically determines an upper bound on the quality of the final problem solution. As a consequence, a strong demand for advanced modeling and identification schemes arises. Moreover every model is developed as a problem dependent solution, in other words, many aspects of a system can be modeled and on the basis of the specific problem a model is determined.

Ключевые слова: modeling, nonlinear systems, Automatic Control, Neural Networks, identification, Fault detection and diagnosis, Resource allocating network, Dictrete-time Sliding Mode Control