Unknown time-varying input delay compensation for uncertain nonlinear systems

Obuz, Serhat; Klotz, Justin R.; Kamalapurkar, Rushikesh; Dixon, Warren E.

doi:10.1016/j.automatica.2016.09.030

Cited by 95 publications

(61 citation statements)

References 41 publications

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“…21,[27][28][29]47 Actually, for general mechanical systems, the function f(x) usually represents structural behaviors, such as motion flow in hydraulic actuation systems and mechanism nonlinearity in manipulators etc and can be modeled and/or identified offline to a satisfactory level. That is to say, for most mechanical systems, we can always capture some model information, and the inherent model/identification error can be lumped to the additive disturbance term.…”

Section: Remarkmentioning

confidence: 99%

“…Similar assumptions can also be found in previous studies. [27][28][29] 3 | OUTPUT FEEDBACK CONTROLLER DESIGN…”

Section: Remarkmentioning

confidence: 99%

“…To cope with this issue, a judicious robust tracking controller in Sharma et al 21 was proposed for an uncertain Euler-Lagrange system with constant input delay by using a predictor-like feedback term to compensate for the input delay. The stability analysis using LK functionals was provided to prove that semiglobally uniformly ultimately bounded tracking performance can be achieved by the controller in Sharma et al 21 In view of the fact that the practical systems may be subject to time-varying delay in the control input, Fischer et al 27 and Obuz et al 28 extended the control method in Sharma et al 21 to solve this problem based on the assumption that the change rate of the input delay is bounded by a known bound. Moreover, time-varying input and state delay compensation for uncertain disturbed nonlinear systems was also realized in Kamalapurkar et al 29 However, all aforementioned controllers are developed under the assumption of accessibility of full state information for feedback.…”

Section: Introductionmentioning

confidence: 99%

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Time‐varying input delay compensation for nonlinear systems with additive disturbance: An output feedback approach

Deng

Yao

2017

Intl J Robust & Nonlinear

118

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SummaryThis paper addresses the output feedback tracking control of a class of multipleinput and multiple-output nonlinear systems subject to time-varying input delay and additive bounded disturbances. Based on the backstepping design approach, an output feedback robust controller is proposed by integrating an extended state observer and a novel robust controller, which uses a desired trajectory-based feedforward term to achieve an improved model compensation and a robust delay compensation feedback term based on the finite integral of the past control values to compensate for the time-varying input delay. The extended state observer can simultaneously estimate the unmeasurable system states and the additive disturbances only with the output measurement and delayed control input. The proposed controller theoretically guarantees prescribed transient performance and steady-state tracking accuracy in spite of the presence of time-varying input delay and additive bounded disturbances based on Lyapunov stability analysis by using a LyapunovKrasovskii functional. A specific study on a 2-link robot manipulator is performed; based on the system model and the proposed design procedure, a suitable controller is developed, and comparative simulation results are obtained to demonstrate the effectiveness of the developed control scheme. | INTRODUCTIONTime delay that includes state delay and input delay is a pervasive phenomenon encountered in many practical engineering applications such as robotic systems, electrical networks, and hydraulic actuation systems. The existence of time delay may result in unexpected degradation in control performance and even instability. 1 Hence, how to effectively attenuate the effect of time delay has always been the research hotspot during the latest several decades, with numerous control schemes proposed, such as previous studies 2-12 for input delay and other studies [13][14][15][16][17][18] for state delay. Especially in Sun et al 17 and Sun and Liu, 18 stabilization of high-order uncertain nonlinear systems with state delays were investigated by using adaptive approach. 19,20 This paper focuses on the problem of input delay, ie, the time delay that occurs between the control input and the plant. Specifically, predictor-based techniques such as Artstein model reduction 2 and finite spectrum assignment, 3 which originate from classic Smith predictor method, 4 are typically exploited to compensate for the input delay. The core design in these predictor-based approaches is to transform the delayed system to a delay free one by using finite integrals over past control values. 21 In addition, many predictive controllers have also been synthesized based on the fact that the input delayed systems can be modeled as

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Section: Remarkmentioning

confidence: 99%

“…Similar assumptions can also be found in previous studies. [27][28][29] 3 | OUTPUT FEEDBACK CONTROLLER DESIGN…”

Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Time‐varying input delay compensation for nonlinear systems with additive disturbance: An output feedback approach

Deng

Yao

2017

Intl J Robust & Nonlinear

118

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“…Considering this factor, some other methods need to be proposed to deal with the input delay. At present, there are a few results reported on uncertain nonlinear systems with input delay . Specifically, a predictor‐based controller, which contained a finite integral of past control value, was developed in References to for a class of uncertain nonlinear systems with matching condition.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neural network tracking control for uncertain nonlinear systems with input delay and saturation

Zhuang

et al. 2020

Intl J Robust & Nonlinear

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In this article, the adaptive tracking control problem is considered for a class of uncertain nonlinear systems with input delay and saturation. To compensate for the effect of the input delay and saturation, a compensation system is designed.Radial basis function neural networks are directly utilized to approximate the unknown nonlinear functions. With the aid of the backstepping method, novel adaptive neural network tracking controllers are developed, which can guarantee all the signals in the closed-loop system are semiglobally uniformly ultimately bounded, and the system output can track the desired signal with a small tracking error. In the end, a simulation example is given to illustrate the effectiveness of the proposed methods. K E Y W O R D Sinput delay, neural networks, nonlinear systems, saturation INTRODUCTIONIn recent years, adaptive control problem for nonlinear systems has attracted considerable attention and remarkable developments have been obtained in nonlinear control area. Among these results, adaptive control by using backstepping technique has received much attention because of its advantages over the conventional approaches (see References 1-5 and references therein). In addition, fuzzy logic systems and neural network have also be widely used in nonlinear control area due to their ability of approximating unknown nonlinear functions. 6-10 Although fruitful results have been obtained for nonlinear systems, there are still some challenging problems waiting to be solved. It is well known that control problem of input-delayed systems is one of the fundamental problems for time-delay systems because of its practical and theoretical significance. At present, many approaches have been proposed for system with state delay (see References 9-13). However, they all ignored the input delay. Compared with state delay, control problem of input delay is more complicated and the traditional Lyapunov-Krasovskii functional based methods are not effective to deal with the input delay. Therefore, it is noteworthy for us to investigate the systems with input delays. A basic idea in dealing with input delay is the predictor feedback. 14,15 However, traditional predictor-based methods have difficulties in practical implementation because of the distributed term. Therefore, to avoid the infinite-dimensionality of feedback laws, truncated predictor feedback was studied in References 16 to 20 to ignore the distributed term.Although fruitful results have been obtained for linear input-delay systems, the adaptive control problem for uncertain nonlinear system is still a challenging problem because nonlinear systems' states are not easy to be predicted with the existence of the nonlinearity and uncertainty. Considering this factor, some other methods need to be proposed to deal with the input delay. At present, there are a few results reported on uncertain nonlinear systems with input delay. 21-34 Specifically, Int J Robust Nonlinear Control. 2020;30:2593-2610.wileyonlinelibrary.com/journal/rnc

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“…Averaging is a very successful technique that was developed in many contributions (including [5], [7], [9], and [15]) and has been applied to many engineering problems [3], [6]. On the other hand, many systems admit time-varying delays, so several contributions are devoted to systems with timevarying delays, including [2], [12], [13], [14], [16], [17], and [18]. For instance, sampling can be represented as a timevarying delay.…”

Section: Introductionmentioning

confidence: 99%

On Average Values of Time-Varying Delays and a New Representation of Systems with Time-Varying Delays

Mazenc

Malisoff

2019

2019 American Control Conference (ACC)

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Unknown time-varying input delay compensation for uncertain nonlinear systems

Cited by 95 publications

References 41 publications

Time‐varying input delay compensation for nonlinear systems with additive disturbance: An output feedback approach

Time‐varying input delay compensation for nonlinear systems with additive disturbance: An output feedback approach

Adaptive neural network tracking control for uncertain nonlinear systems with input delay and saturation

On Average Values of Time-Varying Delays and a New Representation of Systems with Time-Varying Delays

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