Adaptive digital control of systems with scarce measurements

This paper is motivated by the practical control considerations that scarce measurements or missing measurements of systems are abundant in control systems like chemical process control and network-based control. An auxiliary model based recursive least squares algorithm is derived to estimate the parameters of the input-output representation with scarce measurements. Further, we present an adaptive control scheme for such a linear system with scarce measurements; the parameter estimation-based adaptive control algorithm can achieve virtually asymptotically optimal control and ensure that the closed-loop system is stable and globally convergent. A simulation example is used to demonstrate the effectiveness of the proposed control method.