model reference adaptive control is applied to the control of non-linear systems represented by the Wiener model, wherein the non-linearity is any-order poly-nominal. The adaptive algorithms proposed in this paper gua...
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model reference adaptive control is applied to the control of non-linear systems represented by the Wiener model, wherein the non-linearity is any-order poly-nominal. The adaptive algorithms proposed in this paper guarantee the asymptotic stability of the error between the plant output and that of the referencemodel by using only input and output measurements. The concept of growing at the same rate is applied in the stability proof. Smoothing the output response is also considered. To illustrate the validity, the proposed adaptive algorithms are demonstrated by a numerical example.
This paper presents a new real time modelreference neural control system for laser surface treatments, which allows to improve significantly the uniformity and final quality of the process, reducing the rejection rat...
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This paper presents a new real time modelreference neural control system for laser surface treatments, which allows to improve significantly the uniformity and final quality of the process, reducing the rejection rate and increasing the productivity and efficiency of the treatment. The proposed neural controller essentially allows to assimilate the complex system dynamics to a simple first-order linear system, which can be easily controlled by a conventional proportional, integral and derivative controller, PID, providing exceptional results.
In this work, a model reference adaptive control-based estimated algorithm is proposed for online multi-parameter identification of surface-mounted permanent magnet synchronous machines. By taking the dq-axis equation...
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In this work, a model reference adaptive control-based estimated algorithm is proposed for online multi-parameter identification of surface-mounted permanent magnet synchronous machines. By taking the dq-axis equations of a practical motor as the referencemodel and the dq-axis estimation equations as the adjustable model, a standard model-reference-adaptive-system-based estimator was established. Additionally, the Popov hyperstability principle was used in the design of the adaptive law to guarantee accurate convergence. In order to reduce the oscillation of identification result, this work introduces a first-order low-pass digital filter to improve precision regarding the parameter estimation. The proposed scheme was then applied to an SPM synchronous motor control system without any additional circuits and implemented using a DSP TMS320LF2812. For analysis, the experimental results reveal the effectiveness of the proposed method.
This paper puts forward a model reference adaptive control (MRAC) framework with a compensator based on a novel scalar update law for the dynamical systems with matched uncertainty. The scalar update law is given by a...
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This paper puts forward a model reference adaptive control (MRAC) framework with a compensator based on a novel scalar update law for the dynamical systems with matched uncertainty. The scalar update law is given by an algebraic expression of basis functions and system errors. The main advantage of the proposed MRAC framework is that only a scalar function requires updating online such that the architecture is simple and the computational burden in the existing results can be relieved. Furthermore, the asymptotic stability of the system error dynamics is guaranteed by the proposed controller. Two numerical examples are given to demonstrate the effectiveness of the proposed MRAC framework.
In the paper, a cost function of the output error (i.e. the difference between the referencemodel output and the plant output) and weighting control input is minimised in the model reference adaptive control, without...
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In the paper, a cost function of the output error (i.e. the difference between the referencemodel output and the plant output) and weighting control input is minimised in the model reference adaptive control, without the assumption that the unstable plant zeros must be the zeros of the referencemodel. There are two reasons for minimising this cost function: first, to avoid the cancellations of stable plant zeros in the poorly damped region by the closed-loop system poles, for the purpose of preventing a large ripple control input [1], and, secondly, to reduce the effect of disturbance by a suitable choice of weighting function to control input [2]. Two simulation examples are presented to show the good behaviour of this algorithm.
This work is focused on an underwater manipulator. To solve its nonlinear dynamics and hydrodynamics when it operates underwater, model reference adaptive control (MRAC) is applied. The output of the referencemodel r...
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This work is focused on an underwater manipulator. To solve its nonlinear dynamics and hydrodynamics when it operates underwater, model reference adaptive control (MRAC) is applied. The output of the referencemodel represents the expected transient response. adaptivecontroller parameters are adjusted on-line in real time according to the error between the referencemodel output and the system output and the outputs of the state filters, using an adaptive parameter regulator. The system control input is thus achieved such that the system output can track the referencemodel output. Simulation results demonstrate that the proposed control scheme has accurate tracking ability and can greatly improve the dynamic and static properties of the system. The MRAC for the underwater manipulator is also fairly robust to load disturbance and system parameter variation.
A model reference adaptive controller for a twin rotor multiple-input multiple-output system is considered in this article. The objective is to make the twin rotor multiple-input multiple-output system move quickly an...
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A model reference adaptive controller for a twin rotor multiple-input multiple-output system is considered in this article. The objective is to make the twin rotor multiple-input multiple-output system move quickly and accurately to the desired attitudes specified by a referencemodel. Because of the coupling influence between the two axes of the twin rotor multiple-input multiple-output system and its nonlinear complexity, the controller design is performed on the vertical plane and horizontal plane separately. Thus, the nonlinear multiple-input and multiple-output model of the twin rotor multiple-input multiple-output system is decoupled into two subsystems, and the cross-couplings are considered as disturbances to each other. The obtained two models are transformed via Lie derivatives to a canonical form required for adaptivecontroller design. Then, a hyperstability-based adaptivecontrol technique is applied for each subsystem. The proposed controller design is evaluated in simulations of cross-coupled condition. The obtained results show that the controlled system is robust against disturbances with high tracking performance.
One of the basic assumptions in stable model reference adaptive control (MRAC) that the relative degree n* of the modeled part of the plant is known exactly and matches that of the referencemodel is relaxed by the de...
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One of the basic assumptions in stable model reference adaptive control (MRAC) that the relative degree n* of the modeled part of the plant is known exactly and matches that of the referencemodel is relaxed by the development of a new MRAC scheme which requires only an upper bound n(u)* for n*. This is done at the expense of updating additional parameters and projecting some of the estimated parameters onto appropriate convex sets in the parameter space These convex sets can be developed without using any a priori knowledge about the plant parameters. Furthermore, when a lower bound n(l)* in addition to an upper bound for n* is known, the number of the estimated parameters can be reduced considerably. The new MRAC scheme guarantees signal boundedness and zero residual tracking error. In addition, it is robust with respect to plant uncertainties provided a modified adaptive law is used to update the controller parameters.
Because friction-induced nonlinearities in positioning systems an generally range of motion-dependent, dual-model or dual-stage strategies are often adopted to deal with the inconsistencies encountered when a system m...
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Because friction-induced nonlinearities in positioning systems an generally range of motion-dependent, dual-model or dual-stage strategies are often adopted to deal with the inconsistencies encountered when a system moves from submicrometer steps (micro mode) to larger scale strokes (macro mode). Although good performance is usually obtained when each model/stage operates in its designed range of motion, a system frequently performs less satisfactorally when operating near the switching point between models or stages. An air-lubricated capstan drive was used in this study to minimize the discrepancy between macro and micro modes, and a single-mode MRAC was developed to control the capstan drive system for precision positioning. Accuracy better than +/-15 nm with no overshooting was achieved in all conditions tested (including 50 nm, 500 nm and 10 mum steps). Disturbance resistance of the system also proved to be satisfactory. (C) 2000 Elsevier Science inc. All rights reserved.
This paper studies the model reference adaptive control for a class of switched linear systems with uncertain parameters under the dwell time switching. Firstly, the sufficient conditions for the modelreference adapt...
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This paper studies the model reference adaptive control for a class of switched linear systems with uncertain parameters under the dwell time switching. Firstly, the sufficient conditions for the model reference adaptive control synthesis are derived by introducing the time-varying Lyapunov function with increase coefficient in the framework of dwell time technique, where the dwell time is an arbitrary prespecified constant. Secondly, an adaptivecontroller is proposed to ensure that the state of the switched system asymptotically track the state of the reference switched system. Thirdly, based on the Lyapunov function proposed, the lower bound of dwell time is restricted, the decrease of Lyapunov function between two consecutive switched times of the active subsystem is limited, the energy of the whole switched system is reduced, and the asymptotic stability of the error system is realized. Then, if the reference is persistently exciting, the closed-loop error system is asymptotically stable and the parameter estimation error asymptotically converges to zero. Finally, an electro-hydraulic system is taken as an example to verify the effectiveness of the proposed method.
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