Adaptive control of dual-rate systems based on least squares methods

This paper is motivated by a practical control problem that the output sampling rate is often limited. In particular, for a dual-rate system in which the output sampling period is an integer multiple of the input updating period, we use a polynomial transformation technique to obtain a frequency-domain model. Based on this model, we propose a self-tuning control algorithm by minimizing output tracking error criteria from directly the dual-rate input-output data, analyze convergence properties of the algorithm in detail in the stochastic framework, and show that the control algorithm can achieve virtually asymptotically optimal control, ensure the closed-loop systems to be globally convergent and stable, and the output tracking error at the output sampling instants has the property of minimum variance. The results from simulation are included.