โ Scribed by Meryem Makoudi; Larbi Radouane
No coin nor oath required. For personal study only.
In this paper, we present an indirect model reference adaptive control for SISO non-minimum phase systems with unknown or time-varying time delay. The parameter estimation scheme is a combined adaptive data "ltering with a recursive least-squares algorithm with parameter projection and signal normalization. The problem of minimum phase of the plant is handled by an adaptive input}output data "ltering. Hence, the zeros of the system-estimated model are relocated inside the unit circle. This estimated model, which is minimum phased, is then used for the control synthesis. It is shown that the adaptive input}output data "ltering permits also to solve the di$cult problem of model reference adaptive control in the case of unknown time-varying delay. The scheme robustness with respect to unmodelled dynamics and additive noise is also simultaneously improved. Finally, the results are illustrated by numerical examples.
๐ SIMILAR VOLUMES
speed-gradient approach is introduced. The global stability of the overall system is established under the persistency of excitation condition.
In the present paper, a design method of model reference adaptive controllers for processes with uncertain relative degrees r, r#1 or r#2 (r3N), and with unknown signs of high-frequency gains, is presented. This is an extension of Morse's adaptive controllers where it was assumed that the relative d