Direct adaptive controller for uncertain MIMO dynamic systems with time-varying delay and dead-zone inputs

Li, Zhijun; Chen, Ziting; Fu, Jun; Sun, Changyin

doi:10.1016/j.automatica.2015.10.036

Cited by 93 publications

(23 citation statements)

References 17 publications

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“…Recalling the above limitations, an adaptive relative velocity estimation (ARVE) algorithm is presented in the current article. Adaptive techniques have been already developed as controller methods [19][20][21][22][23][24] as well as observer algorithms [25][26][27][28] in diverse applications. [29][30][31][32] Here, an adaptive technique is incorporated in a solution for problem of relative velocity estimation for aerial AMRs.…”

Section: Discussionmentioning

confidence: 99%

Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

Safaei

2020

Adaptive Control & Signal

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Summary In this article, an adaptive algorithm is proposed for online velocity estimation of the autonomous mobile robots (AMRs) without positioning data received from a Global Positioning System (GPS) module or other means for odometry. Unlike the popular Kalman and particle filters that use the measurements on vectors of global (or local) position and acceleration of a mobile robot, the proposed adaptive relative velocity estimation (ARVE) algorithm requires the scalar value of measured distance to a beacon agent and also the measurement on acceleration vector, in order to generate an online estimation of the global velocity vector of a mobile robot. Combining the ARVE algorithm with the recently proposed adaptive relative position estimation (ARPE) algorithm provides a solution for online estimation of the translational states of a mobile robot without accessing the GPS data, which makes the package applicable in both indoor and outdoor environments. The stability of the ARVE algorithm is analyzed with LaSalle‐Yoshizawa theorem. In addition, two simulation studies are provided to show the application of the proposed estimation package (ARVE+ARPE) for aerial AMRs in two cases corresponding to the stationary and moving beacon agents. In the simulation results, it is shown that the estimation package can be used in conjunction with the recently proposed adaptive model‐free control (AMFC) algorithm to achieve desired tracking objective in autonomous movement of a quadrotor, without requiring the information on the internal dynamics of the robot.

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Section: Discussionmentioning

confidence: 99%

Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

Safaei

2020

Adaptive Control & Signal

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“…Over the past decades, many researchers have paid attention to the study of time‐varying delay systems because time delay is often encountered in many practical systems such as network systems, Takagi‐Sugeno fuzzy systems, and nonlinear systems (see other works). Thus far, many results on time‐varying delay systems have been reported in terms of a variety of methods . On the other hand, studies on the tracking control of time‐delay systems have also received considerable attention because tracking control designs are also important issues for practical applications, for example, in robotic tracking control, flight tracking control, and attitude tracking control of aircraft …”

Section: Introductionmentioning

confidence: 99%

Output feedback preview control for polytopic uncertain discrete‐time systems with time‐varying delay

Yuan

2019

Intl J Robust & Nonlinear

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Summary This paper considers the preview tracking control problem of polytopic uncertain discrete‐time systems with a time‐varying delay subject to a previewable reference signal. First, a model transformation is employed and a discrete‐time system with a time‐invariant delay and an external disturbance is obtained. The difference operator method can be extended to derive an augmented error system that includes future information on the reference signal. Then, a previewable reference signal is fully utilized through reformulation of the output equation while considering the output feedback. Based on the small gain theorem, a static output feedback controller with preview actions is designed such that the output can asymptotically track the reference signal. Finally, numerical simulation examples also illustrate the superiority of the desired preview controller for the uncertain system in the paper.

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“…Considering nonsymmetric dead‐zone input and symmetric dead zone input, Boulkroune proposed two fuzzy adaptive variable structure control methods for uncertain multiple‐input and multiple‐output nonlinear systems. In order to ensure the tracking performance, Li et al presented an adaptive control method in which a new high‐dimensional integral Lyapunov‐Krasovskii functional was designed to guarantee the stability of the nonlinearly parameterized dynamic systems with unknown nonlinear dead‐zone inputs. An adaptive neural network control strategy was developed in the work of Li et al for uncertain nonstrict‐feedback nonlinear stochastic systems with output constraint and unknown dead zone.…”

Section: Introductionmentioning

confidence: 99%

Nussbaum gain adaptive backstepping control of nonlinear strict‐feedback systems with unmodeled dynamics and unknown dead zone

Liang

et al. 2018

Intl J Robust & Nonlinear

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Summary This paper investigates an adaptive state feedback control problem for a class of single‐input and single‐output nonlinear systems with strict‐feedback form. A novel adaptive control strategy is developed for nonlinear systems with unmodeled dynamics, unknown control directions, dynamic disturbances and unknown dead zone. To stabilize this category of systems, a dynamic signal is introduced to dominate the unmodeled dynamics. Nussbaum gain technique is used to overcome the unknown control directions problem. Nonlinear damping terms are framed to counteract the dynamic disturbances, and the assistant signal is constructed to compensate the influence of symmetric dead zone. The adaptive control approach ensures all signals in the closed‐loop system to be bounded. Finally, a numerical example is used to verify the effectiveness of the theoretical results.

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Direct adaptive controller for uncertain MIMO dynamic systems with time-varying delay and dead-zone inputs

Cited by 93 publications

References 17 publications

Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

Adaptive relative velocity estimation algorithm for autonomous mobile robots using the measurements on acceleration and relative distance

Output feedback preview control for polytopic uncertain discrete‐time systems with time‐varying delay

Nussbaum gain adaptive backstepping control of nonlinear strict‐feedback systems with unmodeled dynamics and unknown dead zone

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