Showing papers by "Mark J. Balas published in 1983"
TL;DR: In this paper, the model reference adaptive control procedures that do not require explicit parameter identification for large structural systems are considered. But the authors show that this constraint is overly restrictive and that only positive realness is required.
Abstract: Attention is given to model reference adaptive control procedures that do not require explicit parameter identification for large structural systems. Even though such applications have been shown to be feasible for multivariable systems, provided there exists a feedback gain matrix that makes the resulting input/output transfer function strictly positive real, it is shown here that this constraint is overly restrictive and that only positive realness is required. Subsequent consideration of a simply supported beam reveals that if actuators and sensors are collocated, then the positive realness constraint will be satisfied and the model reference adaptive control will then indeed be suitable for velocity following when only velocity sensors are available and for both position and velocity following when velocity plus scaled position outputs are measured. For both cases, all states are guaranteed to be stable, regardless of system dimension.
111 citations
TL;DR: In this article, the Galerkin reduced-order model is used to develop a finite-dimensional controller for distributed parameter systems (DPS), and the stability of this controller in closed-loop with the actual DPS is analyzed.
79 citations
01 Jan 1983
TL;DR: In this article, the authors review and extend fractional representation theory for finite dimensional control of a class of linear evolution equations on a Banach space and present robustness results for internal stability.
Abstract: This paper reviews and extends fractional representation theory. In particular, new and powerful robustness results are presented. This new theory is utilized to develop a preliminary design methodology for finite dimensional control of a class of linear evolution equations on a Banach space. We design for stability in an input-output sense but pay particular attention to internal stability as well.
30 citations
22 Jun 1983
TL;DR: The Kreisselmeier discrete adaptive observer is analyzed for the case in which the observer order is less than that of the plant, and conditions sufficient for ultimate boundedness of the observation errors are given.
Abstract: The Kreisselmeier discrete adaptive observer is analyzed for the case in which the observer order is less than that of the plant. The state and parameter estimates from the observer are compared to the states and parameters for an arbitrary reduced-order model (ROM) of the plant, where the observer and ROM are of equal dimension. Conditions sufficient for ultimate boundedness of the observation errors are given, and expressions for the error bounds are derived.