43 research outputs found

    Convergence and frequency-domain analysis of a discrete first-order model reference adaptive controller

    Get PDF
    SUMMARY We study the convergence properties of a direct model reference adaptive control system by applying techniques from numerical analysis. In particular, a first-order discrete system coupled to a minimal control synthesis algorithm discretized by the one-step one-stage zero-order-hold sampling is studied. This results in a strongly non-linear dynamic system owing to the adaptive mechanism where stability at steady state, i.e. at the operating point, equates to successful control. This paper focuses on the convergence analysis of the overall dynamical system for understanding accuracy, stability and performance at steadystate. The local stability of the steady state solution is considered by linearizing the system in the neighbourhood of an operating point when the input is a step function. This analysis allows us to specify two gain space domains which define the region of local stability. Moreover, both the accuracy and the frequency-domain analyses give insight into the range of adaptive control weightings that results in optimal performance of the minimal control synthesis algorithm and also highlights a possible approach to a priori selection of the time step and adaptive weighting values. The effectiveness of the proposed analysis is further demonstrated by simulations and experiments on a first-order plant. Copyright # 2006 John Wiley & Sons, Ltd

    Synthesised H

    No full text

    A New Extended Minimal Control Synthesis Algorithm with an Application to the Control of a Chaotic System

    No full text
    This paper investigates an extension to the minimal control synthesis (MCS) algorithm (Stoten and Benchoubane, 1990), for the control of systems with rapidly varying disturbances (plant nonlinearities, parameter variations and external inputs), namely a switching action whose amplitude is adaptively estimated is added to the original MCS control law. Proof of global asymptotic stability of the error dynamics is given and the algorithm is applied to the problem of controlling a chaotic system. The results are contrasted with those obtained by applying a standard MCS law
    corecore