Design of Robust Supertwisting Algorithm Based Second-Order Sliding Mode Controller for Nonlinear Systems with Both Matched and Unmatched Uncertainty

Jouini, Marwa; Dhahri, Slim; Sellami, Anis

doi:10.1155/2017/1972921

Cited by 17 publications

(12 citation statements)

References 24 publications

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“…Moreover, several clinical trials have been done by using this methodology and investigate its effectivity [20][21][22]. Linear Parameter Varying (LPV) modelbased solutions have high importance, since the uncertainties can be handled with high efficiency by them [7,9,23]. The Tensor Product (TP) model-based techniques also represent interesting directions, since they can be combined by Linear Matrix Inequality (LMI) based control and LPV methodology as well [24,25].…”

Section: Introductionmentioning

confidence: 99%

Receding Horizon Control of Type 1 Diabetes Mellitus by Using Nonlinear Programming

et al. 2018

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Receding Horizon Controllers are one of the mostly used advanced control solutions in the industry. By utilizing their possibilities we are able to predict the possible future behavior of our system; moreover, we are able to intervene in its operation as well. In this paper we have investigated the possibilities of the design of a Receding Horizon Controller by using Nonlinear Programming. We have applied the developed solution in order to control Type 1 Diabetes Mellitus. The nonlinear optimization task was solved by the Generalized Reduced Gradient method. In order to investigate the performance of our solution two scenarios were examined. In the first scenario, we applied “soft” disturbance—namely, smaller amount of external carbohydrate—in order to be sure that the proposed method operates well and the solution that appeared through optimization is acceptable. In the second scenario, we have used “unfavorable” disturbance signal—a highly oscillating external excitation with cyclic peaks. We have found that the performance of the realized controller was satisfactory and it was able to keep the blood glucose level in the desired healthy range—by considering the restrictions for the usable control action.

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Section: Introductionmentioning

confidence: 99%

Receding Horizon Control of Type 1 Diabetes Mellitus by Using Nonlinear Programming

et al. 2018

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“…wherêˆˆˆˆ 1(2) ( ) (5), the IT2-AFSs described by equations (6) and (21), and the adaptation laws given by equations (13) and (24), then, the global control law presented by equation (23) ensures the stability of the closed loop system with the best tracking performance while avoiding the chattering, despite all the constraints that influence the control system, such as unknown dynamics, approximation errors and unknown disturbances.…”

Section: Interval Type-2 Adaptive Fuzzy Super Twistingmentioning

confidence: 99%

“…Indeed, the large gains values generate a big chattering in the control system and the small ones damage the system robustness, and can even lead to the instability of the closed loop control system. In [24], two terms are added to the conventional STC algorithm to guarantee the desired performance for uncertain nonlinear systems. And most recently, in [25], based on STC algorithm and a high order sliding mode observer, a robust controller-observer is proposed for an uncertain unmanned aerial system to ensure the desired tracking performance.…”

Section: Introductionmentioning

confidence: 99%

Design of a robust interval type-2 fuzzy adaptive super twisting control for a given class of disturbed MIMO nonlinear systems

Nafia¹,

El²,

Ayyad³

et al. 2020

FME Transactions

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This study deals with the tracking control problem of a large class of multi input multi output (MIMO) nonlinear systems with unknown dynamics and subject to unknown disturbances. First, two interval type-2 adaptive fuzzy systems (IT2-AFSs) are constructed to efficiently estimate the unknown nonlinear dynamics. Then, based on IT2-AFSs and super-twisting algorithm (STA), a new robust adaptive fuzzy-reaching STC law (AF-RSTCL) has been added to the global control law to improve the robustness of the studied systems in the presence of approximation errors and unknown disturbances. In order to avoid the chattering phenomenon and guarantee simultaneously the best tracking performance, the gains of the designed AF-RSTCL are optimally online estimated. The adaptive parameters of the global synthesized control law are deduced from the stability analysis in the sense of Lyapunov. Finally, an example of simulation is used to confirm the effectiveness of the developed method in achieving the predetermined objectives of the tracking control.

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“…In [15]- [16], the sliding functions based on the occurrence probability of packet dropout occurred in state feedback side have been constructed, where the reachability conditions have been given by adopting a novel Lyapunov function with respect to system states and sliding function variables. By considering the effects from the matched and unmatched uncertainties (MUU), Jouini et al [17] proposed a novel super-twisting algorithm based on a second-order SMC. Moreover, Karami-Mollaee et al [18] introduced multiple sliding surfaces with virtual inputs to overcome the mismatched uncertainty, and utilized an integrator to solve the chattering issue.…”

Section: Introductionmentioning

confidence: 99%

Design of Adaptive Distributed Secondary Control Using Double-Hidden-Layer Recurrent-Neural-Network-Inherited Total-Sliding-Mode Scheme for Islanded Micro-Grid

Zhang

Wai

2022

IEEE Access

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This study proposes an adaptive double-hidden-layer recurrent-neural-network (DRNN)-based distributed secondary control (ADRNN-SC) scheme for the voltage restoration and the optimal active power sharing in an islanded micro-grid (MG). Based on the dynamic model composed of MG network model and primary control, a total-sliding-mode (TSMC)-based distributed secondary control (TSMC-SC) scheme is firstly developed for the properties of fast convergence and overall robustness during the control process, where the issues of voltage restoration and optimal active power sharing are converted to local-neighborhood synchronization and tracking problems. Meanwhile, focused on the problems of the control chattering phenomenon and the model dependence, a model-free DRNN structure is used to mimic the designed TSMC-SC law and to inherit its robust performance. The double-hidden-layer neural network (NN) in the DRNN structure needs less neuron nodes than the one with a single hidden layer at the same control performance because of its strong presentation ability. Thus, the computational complexity of the proposed ADRNN-SC scheme can be reduced. Moreover, the recurrent loop in the DRNN structure delivers the feedback signals of the output layer to the input layer, which possesses associative memory and accelerates the convergence process. Therefore, the DRNN structure can engage with a strong approximation ability and superior dynamic performance. In addition, the network parameters are online tuned adaptively to enhance the network learning ability. Furthermore, based on the small-signal model of the proposed control method embedded with communication delays, the delay margin and the influence of control parameters are also investigated. The effectiveness of the proposed control method is verified by numerical simulations.INDEX TERMS Double-hidden-layer recurrent-neural-network (DRNN), islanded micro-grid (MG), distributed secondary control, small-signal analysis, total sliding-mode control (TSMC).

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Design of Robust Supertwisting Algorithm Based Second-Order Sliding Mode Controller for Nonlinear Systems with Both Matched and Unmatched Uncertainty

Cited by 17 publications

References 24 publications

Receding Horizon Control of Type 1 Diabetes Mellitus by Using Nonlinear Programming

Receding Horizon Control of Type 1 Diabetes Mellitus by Using Nonlinear Programming

Design of a robust interval type-2 fuzzy adaptive super twisting control for a given class of disturbed MIMO nonlinear systems

Design of Adaptive Distributed Secondary Control Using Double-Hidden-Layer Recurrent-Neural-Network-Inherited Total-Sliding-Mode Scheme for Islanded Micro-Grid

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