Adaptive control

Related papers: 20

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Adaptive control is a class of control strategies in which the controller continuously adjusts its parameters in real time to accommodate unknown or changing system dynamics. Rather than relying on a fixed, pre-tuned model, adaptive controllers estimate uncertain parameters—such as robot link masses, friction coefficients, or payload variations—online and update the control law accordingly. In robotics and AI, adaptive control is widely applied to robot manipulators, mobile robots, underwater vehicles, and aerial systems, where dynamic uncertainties and environmental disturbances make fixed controllers unreliable. Common approaches include model reference adaptive control, adaptive sliding-mode control, and neural network or fuzzy-based adaptive schemes that approximate unknown nonlinearities. These methods are often combined with techniques like backstepping, impedance control, or prescribed performance frameworks to handle constraints and guarantee stability. Adaptive control matters because real-world robots operate under conditions that cannot be perfectly modeled in advance; by learning and compensating for uncertainties on the fly, adaptive controllers deliver robust, high-performance tracking and safety even as operating conditions evolve.

Top Cited Papers

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Jean-Jacques Slotine, Weiping Li

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The attitude control problem

John T. Wen, Kenneth Kreutz-Delgado

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Robot Manipulator Control: Theory and Practice

Frank L. Lewis, D.M. Dawson, Chaouki T. Abdallah

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Tracking Control of Mobile Robots: A Case Study in Backstepping**This paper was not presented at any IFAC meeting. This paper was recommended for publication in revised form by Associate Editor Alberto Isidori under the direction of Editor Tamer Başar.

ZHONG-PING JIANGdagger, Henk Nijmeijer

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Full control of a quadrotor

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Design and control of quadrotors with application to autonomous flying

Samir Bouabdallah

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Rafael Fierro, Frank L. Lewis

Citations: 714 • 1998

Adaptive Fixed-Time Control for MIMO Nonlinear Systems With Asymmetric Output Constraints Using Universal Barrier Functions

Xu Jin

Citations: 679 • 2018

Control of a nonholonomic mobile robot: backstepping kinematics into dynamics

Rafael Fierro, Frank L. Lewis

Citations: 658 • 2002

Leader–follower formation control of underactuated autonomous underwater vehicles

Rongxin Cui, Shuzhi Sam Ge, Bernard Voon Ee How, Yoo Sang Choo

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Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning

Wei He, Yiting Dong

Citations: 638 • 2017