Self-optimizing control provides nearly optimal operation of process systems in the face of varying disturbances, where the inputs are adjusted to hold selected controlled variables (c) at constant setpoints. It is possible to have better self-optimizing properties by controlling linear combinations of measurements (c = Hy) than by controlling individual measurements. Previous work focused on selecting combination matrix H to minimize worst-case loss, that arises due to the use of suboptimal self-optimizing control policy. In this paper, we present a method for finding combination matrix H that minimizes average loss for local self-optimizing control. It is further shown that the combination matrix that minimizes average loss is superoptimal in the sense that it also minimizes worst-case loss simultaneously. The usefulness of the results is demonstrated using an evaporator case study.

499and amplitudes of sinusoids. As proved, both types of the estimators and observers possess the property of global convergence. Although the amplitude estimators are conceptually and computationally simpler than the amplitude observers, the latter avoids a critical step in calculations of the inverse of the Vandermonde matrix and hence can better deal with the cases when two or more estimated sinusoidal frequencies are close to each other. Nevertheless, the amplitude observers have the drawback of slowing down the estimation process, and still freezing when the determinant of the Vandermonde matrix approaches zero.Essentially, the proposed method is a two-step approach to the underlying problem. In the first step, frequency estimation is carried out, while in the second step, amplitudes are estimated on the basis of the outcomes of the frequency estimation. Because of possible numerical problems in estimating individual sinusoidal components, the two-step method is perhaps less efficient than the frequency and amplitude estimator in [7] which applies to a single sinusoid only. An analogy of the treatment of a single sinusoid is still missing for the case of multiple sinusoids.The proposed amplitude estimators and amplitude observers appear to be the first solutions of the underlying estimation problem with the property of global asymptotic convergence, whilst applications of the methods in a wide range of scientific and engineering disciplines demand exploitations. Control, vol. 47, no. 7, pp. 1188-1193, Jul. 2002 R. Marino and P. Tomei, "Global estimation of n unknown frequencies," IEEE Trans. Autom. Control, vol. 47, no. 8, pp. 1324-1328, Aug. 2002 L. Hsu, R. Ortega, and G. Damm, "A globally convergent frequency estimator," IEEE Trans. Autom. Control, vol. 44, no. 4, pp. 698-713, Apr. 1999. [7] M. Hou, "Amplitude and frequency estimator of a sinusoid," IEEE Trans. Autom. Control, vol. 50, no. 6, pp. 855-858, Jun. 2005 Control, vol. 34, no. 4, pp. 435-443, Apr. 1989. [12] Abstract-Over the last few years, the research on discrete-time sliding mode control has received a considerable attention. Unlike its continuoustime counterpart, discrete-time sliding mode control is not invariant in general. In this note, an algorithm is presented for robust discrete-time sliding mode control using the concept of multirate output feedback. REFERENCESIndex Terms-Discrete-time systems, multirate output feedback, slidingmode control (SMC), uncertain systems.

No abstract

No abstract

Abstract-In terminal sliding-mode control, the system states are brought to the origin in finite time using the concept of sliding-mode control. Though the theory of terminal sliding mode is well studied for continuous time systems, a discrete-time terminal sliding mode concept has not been investigated. This note analyses the applicability of terminal sliding-mode control in the discrete-time framework and discusses the problems involved in the discretization of continuous-time terminal sliding mode. The note also suggests a method to approach the discrete-time terminal sliding-mode control problem.