Robust analysis of Principal Components active control via IQCs

Principal Component algorithms are widely used in active control applications, specially for applications of active vibration and noise cancellation in the aerospace industry. They are known to offer good adaptability characteristics and also provide a intuitive approach to deal with actuator saturation by limiting the control only to a significant number of modes. Existing stability results for such PC applications are only provided for nominal scenarios and plant uncertainty. The contribution of this paper is to apply the theory of Integral Quadratic Constraints (IQCs) in order to find more general stability criteria when scaling of the control actions take place and estimation of modelling errors coexist. The robustness criterion is expressed as an Linear Matrix Inequality. Stability results are shown with a simulation example.