Control of MIMO nonlinear discrete-time systems with input saturation via data-driven model-free adaptive fast terminal sliding mode controller

Esmaeili, Babak; Salim, Mina; Baradarannia, Mahdi

doi:10.1109/icee50131.2020.9260928

Cited by 4 publications

(6 citation statements)

References 28 publications

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“…Understanding the control system's mathematical model is necessary for designing SMC controllers. \Therefore, designing SMC based on CFDL data models is of great significance for simultaneously leveraging their advantages [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Model-Free Adaptive Nonsingular Fast Integral Terminal Sliding Mode Control for Wastewater Treatment Plants

Xu,

Wang,

Liu

et al. 2023

Applied Sciences

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The regulation of wastewater treatment plants (WWTPs) is a challenge due to their complex biological and chemical characteristics and their accurate mathematical model is generally not accessible because of the limitation of available measurements. To overcome such challenges, in this paper, a novel model-free adaptive nonsingular fast integral terminal sliding mode control (MFA-NFITSMC) is proposed. Firstly, based on the concept of dynamic linearization, a compact format dynamic linearized (CFDL) data model for the WWTP is established. Secondly, a novel fast integral terminal sliding mode surface is proposed to accelerate the convergence of tracking error and a discrete-time MFA-NFITSMC is created using the CFDL model as a basis; then, its stability is proved by theoretical analysis. Finally, the experimental verification is conducted based on the Benchmark Simulation Model No. 1 and the results show that the proposed method has a higher tracking accuracy and stronger robustness than other methods in the control of WWTPs.

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Section: Introductionmentioning

confidence: 99%

Model-Free Adaptive Nonsingular Fast Integral Terminal Sliding Mode Control for Wastewater Treatment Plants

Xu,

Wang,

Liu

et al. 2023

Applied Sciences

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“…Furthermore, by taking nonlinear sliding surfaces into account, DL-based finite-time DSMCs have been proposed for rigid manipulators driven by PAMs, and the electrically actuated ones in Esmaeili et al (2019a) and Esmaeili et al (2019b), respectively, to gain higher precision and finite-time convergence. A constrained fast-terminal sliding surface–based MFAC has also been developed in Esmaeili et al (2020). From the iteration point of view, in Chi et al (2019), an optimization-based model-free adaptive iterative learning sliding mode control has been designed for SISO plants, and its extension to MIMO systems has been proposed in Wang et al (2020a).…”

Section: Introductionmentioning

confidence: 99%

“…However, these control methods are commonly designed based on a priori knowledge about the robots' implicit/ explicit models which are often unavailable, or it is laborious to achieve them. In the literature, there exist several data-based techniques, such as virtual-reference feedback tuning (Radac and Precup, 2018), subspace predictors (Salim and Esmaeili, 2020;Salim and Khosrowjerdi, 2017), and dynamic linearization (Hou and Xiong, 2019;Yu et al, 2020b), which only rely on the plants' measurement data.…”

Section: Introductionmentioning

confidence: 99%

Model-free adaptive iterative learning integral terminal sliding mode control of exoskeleton robots

Esmaeili

Madani

Salim

et al. 2021

Journal of Vibration and Control

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This article addresses the reference tracking issue of multi-degree-of-freedom robotic exoskeletons under exogenous perturbations. First, by considering the concept of iteration-dependent full-format dynamic linearization, the exoskeleton robot’s dynamics is reformulated as a linear data model in an iterative manner. Then, based upon an iterative sliding variable, a novel data-based model-free adaptive iterative learning integral terminal sliding mode control is designed. The superiority of the proposed study is that the reference tracking problem is just solved by using the measured input/output information of exoskeletons. In addition, its finite-iteration convergence is also affirmed by mathematical analysis. The simulation investigation together with the compared results also clarifies the efficiency of the developed learning-based control algorithm.

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“…In recent years, many researchers have discovered the aforementioned challenges and the exploration for the solutions to these problems using different techniques, such as fuzzy logic [1][2][3][4][5][6], neural networks [7][8][9], and sliding mode techniques [10][11][12][13][14][15][16][17]. In [18], a novel decentralized optimal control strategy was developed using the online learning of neural networks to stabilize a class of continuous-time nonlinear interconnected large-scale systems.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, a control scheme is proposed based on the decentralized principle in which the input couplings for the uncertain nonlinear MIMO system is first resolved, converting it into decoupled Single-Input-Single-Output (SISO) linear time-invariant systems, then followed by an application of an IADRC for each of the SISO systems separately. This technique has the advantage of reducing model dependence in its design as compared to the aforementioned works [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. The suggested IADRC-based decentralized control configuration does not require a huge tuning to its coefficients similar to the adaptive control methods that are based on neural networks.…”

Section: Introductionmentioning

confidence: 99%

Anti-Disturbance Compensation-Based Nonlinear Control for a Class of MIMO Uncertain Nonlinear Systems

Abdul-Adheem

Alkhayyat

Mhdawi

et al. 2021

Entropy

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Multi-Inputs-Multi-Outputs (MIMO) systems are recognized mainly in industrial applications with both input and state couplings, and uncertainties. The essential principle to deal with such difficulties is to eliminate the input couplings, then estimate the remaining issues in real-time, followed by an elimination process from the input channels. These difficulties are resolved in this research paper, where a decentralized control scheme is suggested using an Improved Active Disturbance Rejection Control (IADRC) configuration. A theoretical analysis using a state-space eigenvalue test followed by numerical simulations on a general uncertain nonlinear highly coupled MIMO system validated the effectiveness of the proposed control scheme in controlling such MIMO systems. Time-domain comparisons with the Conventional Active Disturbance Rejection Control (CADRC)-based decentralizing control scheme are also included.

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Control of MIMO nonlinear discrete-time systems with input saturation via data-driven model-free adaptive fast terminal sliding mode controller

Cited by 4 publications

References 28 publications

Model-Free Adaptive Nonsingular Fast Integral Terminal Sliding Mode Control for Wastewater Treatment Plants

Model-Free Adaptive Nonsingular Fast Integral Terminal Sliding Mode Control for Wastewater Treatment Plants

Model-free adaptive iterative learning integral terminal sliding mode control of exoskeleton robots

Anti-Disturbance Compensation-Based Nonlinear Control for a Class of MIMO Uncertain Nonlinear Systems

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