Extended-State-Observer-Based Output Feedback Nonlinear Robust Control of Hydraulic Systems With Backstepping

Yao, Jianyong; Zhang, Jiao; Ma, Dawei

doi:10.1109/tie.2014.2304912

Cited by 630 publications

(407 citation statements)

References 33 publications

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“…Based on the extended system model (Equation 4), and referring to Yao et al 43 and Zheng et al, 46 a linear extended state observer (LESO) can be constructed as…”

Section: Extended State Observer Designmentioning

confidence: 99%

“…Remark 4 To implement the needed control parameters, there are 2 general ways suggested in Yao et al 43,50 The first method is to pick up a set of k 1 , k 2 , …, k n , k r , and ω 0 to calculate all order sequential principal minor determinants of matrix Λ in Equation 44 to ensure it positive definite. This approach is rigorous and formal approach.…”

Section: Theorem 1 With the Designed Leso In Equationmentioning

confidence: 99%

“…Such superiority has been demonstrated by many engineering applications like in Yao et al 43,44 and Xue et al 45 Especially in Yao et al, 43 a linear type of ESO 46 was incorporated with a nonlinear robust controller via backstepping method to derive an output feedback robust controller for a hydraulic system. The first closed loop stability analysis associated with ESO-based nonlinear controllers was presented to verify the prescribed tracking performance.…”

Section: Introductionmentioning

confidence: 99%

“…Inspired by the work in Yao et al, 43 an output feedback robust controller is proposed in this paper for a class of nth order MIMO nonlinear systems with time-varying input delay and additive bounded disturbances by synthesizing a linear extended state observer (LESO) and a novel robust controller based on backstepping design. The virtual control laws and the final control input are developed based on the estimated states acquired from the LESO that only depends on the output measurement and delayed control input.…”

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

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119

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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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“…Based on the extended system model (Equation 4), and referring to Yao et al 43 and Zheng et al, 46 a linear extended state observer (LESO) can be constructed as…”

Section: Extended State Observer Designmentioning

confidence: 99%

Section: Theorem 1 With the Designed Leso In Equationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Deng

Yao

2017

Intl J Robust & Nonlinear

Self Cite

119

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“…17 We have to mention that there are other methods based on constrained adaptive control approaches that can solve the constrained control problem posed in this work. [18][19][20][21] In this work, the model predictive controller with constraints on the control signal is used to control the water level of a tank over an RF link. We note that we are using only a single system instead of multiple systems (network).…”

Section: Introductionmentioning

confidence: 99%

Wireless model predictive control: Application to water-level system

Hedjar

Bounkhel

2016

Advances in Mechanical Engineering

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This article deals with wireless model predictive control of a water-level control system. The objective of the model predictive control algorithm is to constrain the control signal inside saturation limits and maintain the water level around the desired level. Linear modeling of any nonlinear plant leads to parameter uncertainties and non-modeled dynamics in the linearized mathematical model. These uncertainties induce a steady-state error in the output response of the water level. To eliminate this steady-state error and increase the robustness of the control algorithm, an integral action is included in the closed loop. To control the water-level system remotely, the communication between the controller and the process is performed using radio channel. To validate the proposed scheme, simulation and real-time implementation of the algorithm have been conducted, and the results show the effectiveness of wireless model predictive control with integral action.

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References

2016

Active Disturbance Rejection Control for Nonlinear Systems

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Extended-State-Observer-Based Output Feedback Nonlinear Robust Control of Hydraulic Systems With Backstepping

Cited by 630 publications

References 33 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

Wireless model predictive control: Application to water-level system

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