A Hybrid Robust Adaptive Sliding Mode Controller for partially modelled systems: Discrete-time Lyapunov stability analysis and application

Milbradt, Deise Maria Cirolini; Evald, Paulo Jefferson Dias de Oliveira; Hollweg, Guilherme Vieira; Gründling, Hilton Abílio

doi:10.1016/j.nahs.2023.101333

Cited by 24 publications

(10 citation statements)

References 41 publications

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“…To analyze the position-tracking performance of the proposed ASMC method, considering the comparative results of the reference tracking on other controllers [ 44 , 45 ], the comparative results are given in this paper. Figure 5 and Figure 6 , respectively, show the comparative simulation results of the PID, SMC and ASMC methods in tracking step signal and sine signal.…”

Section: Resultsmentioning

confidence: 99%

Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment

Gu,

Wang,

Yan

et al. 2024

Sensors

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This study develops an adaptive sliding mode control approach for a drilling tool attitude adjustment system, aiming at solving the problems of model uncertainties and insufficient ability of disturbance suppression during the regulation behavior. To further improve the performance of the position-tracking loop in terms of response time, tracking accuracy, and robustness, a state observer based on an improved radial basis function is designed to approximate the model uncertainties, a valve dead-zone compensate controller is used to reduce control deviation, an adaptive sliding mode controller is designed to improve the position-tracking precision and attenuate sliding mode chattering. Finally, simulation and experimental results are carried out to verify the observability of the model uncertainties and position-tracking errors of the drilling tool attitude adjustment system, which can effectively improve the position-tracking performance and robustness of the drilling tool attitude adjustment system.

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Section: Resultsmentioning

confidence: 99%

Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment

Gu,

Wang,

Yan

et al. 2024

Sensors

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“…The simplification method is based on Reference 60, where the capacitor dynamics is neglected during controller design. This procedure was also used in References 56,57,62,65,66, aiming to reduce the quantity of parameters to design in their adaptive controllers, which depends on relative degree of chosen reference model that must be the same relative degree of the nominal part of the plant. Different from all these control strategies, the hybrid robust MRAC‐PI controller does not require a reference model, even being a direct adaptive controller, because it can track the reference signal straightforwardly.…”

Section: Simulation Resultsmentioning

confidence: 99%

A hybrid robust model reference adaptive controller and proportional integral controller without reference model for partially modeled systems

Evald

Hollweg

Tambara

et al. 2023

Adaptive Control & Signal

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Summary This work presents the discrete‐time stability analysis of a hybrid robust model reference adaptive controller and proportional‐integral controller (MRAC‐PI) controller using Lyapunov criterion. The control structure merges the classical PI controller with a robust model reference adaptive control, resulting in an adaptive and robust control strategy, where the gains unite both control techniques in a unique structure and it does not require the design of a reference model, being able to track straightforwardly the reference signal. The adaptive gains are updated continuously by a modified gradient algorithm regarding control action, regulation error, and the system output. The stability analysis provides the controller design constraints, while also demonstrate the tendency of regulation error to a residual set, and proves the boundedness of all closed‐loop signals. Furthermore, as the controller is robust to unmodeled dynamics, it is feasible to control partially modeled systems. Simulation results in a real‐world engineering application are presented to corroborate the robustness of this controller and show its fast response in the face of critical exogenous system perturbations.

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“…In order to reduce chattering of SMC, various methods of adaptation of the switching gain can be found in literatures. 12,14,24,46,47 In, 12 the design of an internal model principle-based sliding-mode DOB with switching-gain adaptation law is addressed for a class of nonlinear systems subject to exogenous signals. Utilizing the Lyapunov-Krasovskii functional, 14 designs the observer-based adaptive SMC for nonlinear uncertain singular semi-Markov jump systems, in which two adaptive gains are required.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the barrier function, the distributed consensus for multi-agent systems via adaptive SMC is considered in, 24 in which the control gains can be chosen randomly, whereas the adaptive switching gains are divided into two stages, and they are increasing in the first stage. Robust model reference adaptive control-based techniques, 46,47 study discrete-time hybrid robust adaptive SMC and robust adaptive super-twisting SMC for partially modeled systems, respectively. However, the design of adaptive switching gains mentioned in the above literatures depends on many model parameters and requires lots of calculation.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the constant switching gain also causes some nominal performance sacrifice of the system. In order to reduce chattering of SMC, various methods of adaptation of the switching gain can be found in literatures 12,14,24,46,47 . In, 12 the design of an internal model principle‐based sliding‐mode DOB with switching‐gain adaptation law is addressed for a class of nonlinear systems subject to exogenous signals.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Novel sliding‐mode control for a class of second‐order systems with mismatched disturbances

Fu,

Che,

Liu

et al. 2023

Intl J Robust & Nonlinear

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This article investigates a novel sliding‐mode control (SMC) approach for a class of second‐order nonlinear systems subject to mismatched disturbances. To solve this problem, a novel sliding surface is designed based on the disturbance estimation of the nonlinear disturbance observer (DOB). By designing a novel time‐varying switching gain, a DOB‐based improved SMC law is constructed to compensate the influence of mismatched disturbances on the system output and make the system output converge asymptotically to zero. The novel SMC scheme owns two advantages. One is that the switching gain is an exponential decay function varying synchronously with the disturbance estimation error, which substantially alleviates the chattering problem. The other one is that a new function is defined as the switching gain coefficient based on the disturbance estimation, which helps the proposed approach to maintain the nominal control performance of the system, that is, the novel SMC law degrades to the baseline SMC law in the absence of disturbances. A numerical simulation example verifies the effectiveness and superiority of the developed approach by comparisons.

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A Hybrid Robust Adaptive Sliding Mode Controller for partially modelled systems: Discrete-time Lyapunov stability analysis and application

Cited by 24 publications

References 41 publications

Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment

Observer-Based Adaptive Sliding Mode Compensation Position-Tracking Control for Drilling Tool Attitude Adjustment

A hybrid robust model reference adaptive controller and proportional integral controller without reference model for partially modeled systems

Novel sliding‐mode control for a class of second‐order systems with mismatched disturbances

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