Qualitative Analysis of Chaos in Nonlinear Sampled Data Systems and System Identification
B. R. Haynes, Steve A. Billings · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 1991
The analysis of nonlinear sampled data systems is considered. A qualitative approach is adopted in which the system is suspended in a parameterised cell state space framework. Application of a global unravelling algorithm reveals the type of behaviour typically found using dynamical systems techniques. Steady state, periodic and aperiodic or chaotic behaviour is detected. System identification techniques are then applied. The resulting nonlinear recursive input output model is also analysed within the above framework and shown to exhibit the self same periodic characteristic as the original nonlinear sampled data system.