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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This paper presents an adaptive voltage controller for secondary control (SC) of standalone AC microgrid systems, adaptive parametric estimation features inherent in model reference adaptive control (MRAC) systems. Th...
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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.
In this paper, an observer-based model reference adaptive controller is proposed to solve the vibration control problem for offshore wind turbines. The process begins with the formulation of a dynamic model that accou...
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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-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.
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