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Journal ArticleDOI

Adaptive Control of Electrostatic Microactuators With Bidirectional Drive

TLDR
In this paper, adaptive control is presented for a class of single-degree-of-freedom (1DOF) electrostatic microactuator systems which can be actively driven bidirectionally.
Abstract
In this paper, adaptive control is presented for a class of single-degree-of-freedom (1DOF) electrostatic microactuator systems which can be actively driven bidirectionally. The control objective is to track a reference trajectory within the air gap without knowledge of the plant parameters. Both full-state feedback and output feedback schemes are developed, the latter being motivated by practical difficulties in measuring velocity of the moving plate. For the full-state feedback scheme, the system is transformed to the parametric strict feedback form, for which adaptive backstepping is performed to achieve asymptotic output tracking. Analogously, the output feedback design involved transformation to the parametric output feedback form, followed by the use of adaptive observer backstepping to achieve asymptotic output tracking. To prevent contact between the movable and fixed electrodes, special barrier functions are employed in Lyapunov synthesis. All closed-loop signals are ensured to be bounded. Extensive simulation studies illustrate the performance of the proposed control.

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Citations
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Journal ArticleDOI

Barrier Lyapunov Functions for the control of output-constrained nonlinear systems

TL;DR: This paper presents control designs for single-input single-output (SISO) nonlinear systems in strict feedback form with an output constraint, and explores the use of an Asymmetric Barrier Lyapunov Function as a generalized approach that relaxes the requirements on the initial conditions.
Journal ArticleDOI

Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function

TL;DR: A barrier Lyapunov function (BLF) is introduced to address two open and challenging problems in the neuro-control area: for any initial compact set, how to determine a priori the compact superset on which NN approximation is valid; and how to ensure that the arguments of the unknown functions remain within the specified compact supersets.
Journal ArticleDOI

Brief paper: Control of nonlinear systems with time-varying output constraints

TL;DR: It is shown that asymptotic output tracking is achieved without violation of the time-varying constraint, and that all closed loop signals remain bounded.
Journal ArticleDOI

Barrier Lyapunov Functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints

TL;DR: An adaptive control technique is developed for a class of uncertain nonlinear parametric systems and it is proved that all the signals in the closed-loop system are global uniformly bounded and the tracking error is remained in a bounded compact set.
Journal ArticleDOI

Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems

TL;DR: Two theorems are provided to show that all the signals in the closed-loop system are bounded, the outputs are driven to follow the reference signals and all the states are ensured to remain in the predefined compact sets.
References
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Book

Applied Nonlinear Control

TL;DR: Covers in a progressive fashion a number of analysis tools and design techniques directly applicable to nonlinear control problems in high performance systems (in aerospace, robotics and automotive areas).
Book

Nonlinear and adaptive control design

TL;DR: In this paper, the focus is on adaptive nonlinear control results introduced with the new recursive design methodology -adaptive backstepping, and basic tools for nonadaptive BackStepping design with state and output feedbacks.
Proceedings ArticleDOI

Robust adaptive control

TL;DR: In this article, the authors present a model for dynamic control systems based on Adaptive Control System Design Steps (ACDS) with Adaptive Observers and Parameter Identifiers.
Book

Stable Adaptive Systems

TL;DR: Stability theory simple adaptive systems adaptive observers the control problem persistent excitation error models robust adaptive controlThe control problem - relaxation of assumptions multivariable adaptive systems applications of adaptive control.
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