Adaptive tracking control algorithms for large-scale interconnected nonlinear systems

The present work proposes two control algorithms for a class of large-scale deterministic systems, which are composed into a set of interconnected monovariable systems and defined by discrete oriented block model with variable parameters. The purpose of these control algorithms is to formulate the tracking problem permitting each interconnected system output to pursue a certain time-varying reference trajectory. Each control algorithm is developed with a direct or indirect scheme and is incorporated into a recursive estimator, used to estimate the system parameters. This estimation step is established using the prediction error approach and the least-squares method. A numerical simulation example is cured to validate the developed theoretical results.