Adaptive control with loop transfer recovery: A Kalman filter approach

Abstract

In this paper we develop a Kalman filter based adaptive controller for multivariable uncertain systems with loop transfer recovery of an associated reference system. This approach increases the level of confidence of adaptive control systems by providing a means for preserving stability margins even under uncertainty and failures. In addition, it results in an optimization based time-varying adaptation gain. An example is provided to illustrate the efficacy of the proposed approach.

On adaptive loop transfer recovery using Kalman filter‐based disturbance accommodating control

“…Even though most of the work in the field of LQG/LTR was conducted during the 70-90s, recently, there has been an increased interest in developing robust/adaptive controllers based on the LTR design [8][9][10][11][12][13][14][15]. In [9,10], Lavretsky presents an observer-based adaptive output feedback controller that utilises the asymptotic property of the LQG/LTR.…”

“…Compared to the approach presented by Lavretsky, the proposed approach does not require an adaptive control input, but only requires tuning the process noise intensity matrix. Some of the recent advances in the LTR theory involves, (i) the extension of LTR to H ∞ -control [11], (ii) development of bilinear LTR observers [12], (iii) adaptive LTR synthesis using KF-based adaptive law [13], (iv) generalisation of the LTR procedure to proportional-integral-derivative controllers [14] and (v) LTR-based controller configuration for systems with sensor faults [15]. Moreover, LQG/LTR has been recently applied to robust control of a space launcher [16], oscillation control in power systems [17], temperature control in nuclear reactors [18], throttle control of a gas engine [19] and flight control [20].…”