Cloud-based control is prevalent in many modern control applications. Such applications require security for the sake of data secrecy and system safety. The presented research proposes an encrypted adaptivecontrol fr...
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Electric vertical take-off and landing (eVTOL) aerial vehicles have many practical applications and are a cornerstone of growing research in recent years. These types of vehicles possess highly nonlinear, coupled dyna...
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In this article, we develop a multiple model reference adaptive controller (MMRAC) with blending. The systems under consideration are non-square, i.e., the number of inputs is not equal to the number of states;multi-i...
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The goal of model reference adaptive control (MRAC) is to ensure that the trajectories of an unknown dynamical system track those of a given referencemodel. This is done by means of a feedback controller that adaptiv...
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During the ultraprecise cutting of micro-structure surface with fast tool servo (FTS), the hysteresis of piezoelectric actuators (PEAs) are affected by dynamic voltage excitations and real-time cutting force, which de...
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During the ultraprecise cutting of micro-structure surface with fast tool servo (FTS), the hysteresis of piezoelectric actuators (PEAs) are affected by dynamic voltage excitations and real-time cutting force, which declines the servo accuracy and cutting performance. In this paper, for a multi-input-single-output (MISO) cutting system, a cross-coupling rate-dependent Prandtl-Ishlinskii (CRPI) model is proposed and identified for the dynamic hysteresis of PEAs under dynamic voltage excitation and external loads. A model reference adaptive control method is then presented to eliminate the positioning nonlinearity of PEAs. The hysteresis modeling accuracy is discussed and the adaptivecontroller is validated through experiments.
This work presents an indirect, model reference adaptive control for minimum phase linear systems of arbitrary relative degree. Global stability of the closed-loop system is proved in spite of bounded disturbances and...
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This work presents an indirect, model reference adaptive control for minimum phase linear systems of arbitrary relative degree. Global stability of the closed-loop system is proved in spite of bounded disturbances and asympotic tracking is achieved in the ideal case.
This article presents a switched model reference adaptive controller for discrete-time piecewise linear systems. In the spirit of the work by Landau in the late seventies, proof of asymptotic stability of the closed-l...
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This article presents a switched model reference adaptive controller for discrete-time piecewise linear systems. In the spirit of the work by Landau in the late seventies, proof of asymptotic stability of the closed-loop error system is obtained, recasting its dynamics as a feedback system and showing the feedforward and the feedback paths are both passive. The challenge is that both paths can be piecewise linear. Numerical results show excellent performance of the proposed controller even in the face of sudden variations of the plant parameters. Copyright (c) 2012 John Wiley & Sons, Ltd.
This paper presents the first model reference adaptive control system for nonlinear, time-varying, hybrid dynamical plants affected by matched and parametric uncertainties, whose resetting events are unknown functions...
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This paper presents the first model reference adaptive control system for nonlinear, time-varying, hybrid dynamical plants affected by matched and parametric uncertainties, whose resetting events are unknown functions of time and the plant's state. In addition to a control law and an adaptive law, which resemble those of the classical model reference adaptive control framework for continuous-time dynamical systems, the proposed framework allows imposing instantaneous variations in the referencemodel's trajectory to rapidly steer the trajectory tracking error to zero, while retaining the closed-loop system's ability to follow a user-defined signal. These results are enabled by the first extension of the classical LaSalle-Yoshizawa theorem to time-varying hybrid dynamical systems, which is presented in this paper as well. A numerical simulation shows the key features of the proposed adaptivecontrol system and highlights its ability to reduce both the control effort and the trajectory tracking error over a classical model reference adaptive control system applied to the same problem.
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.
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