Discrete indirect adaptive sliding mode control for uncertain Hammerstein nonlinear systems

Znidi, Aicha; Dehri, Khadija; Nouri, Ahmed Saïd

doi:10.1177/01423312211067801

Cited by 8 publications

(4 citation statements)

References 39 publications

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“…K ij i,j21,2,3,4 stands for different feedback gain compensation coefficients. To clearly express the coupling relationship between each motor, the speed comprehensive evaluation index E 1 is introduced to optimize the DCC [17].…”

Section: Plos Onementioning

confidence: 99%

Research on coupling control of multiple permanent magnet synchronous motors based on NAISMC and SMDO

Hao,

Zhao

2023

PLoS ONE

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The synchronous control system of multi-permanent magnet motor has the characteristics of many parameter variables and mutual coupling. The use of sliding mode control to optimize the parameters in the multi-permanent magnet motor system not only ensures the stability of the system operation, but also improves the control accuracy of the system, which is of great importance in practical applications. Based on this background, the study combines the new adaptive integral sliding mode control (NAISMC) with the improved sliding-mode disturbance observer (SMDO) and uses it for the multi-permanent magnet synchronous motor (MPMSM). In NAISMC, the controller updates and adjusts the parameters of the controller using an adaptive algorithm according to the state of the system and the error signals, which further improves the stability and robustness of the system. SMDO utilizes the principle of the sliding-mode observer to estimate the disturbance of the system, and eliminates the effect of the disturbance on the system by introducing a compensation term. The sliding mode observer calculates the disturbance estimate by comparing the difference between the actual and the estimated outputs. The disturbance estimate is finally used to generate the corresponding compensation signal to eliminate or minimize the effect of the disturbance on the system. NAISMC is combined with SMDO and used in the deviation coupling control of MPMSM. The study established a simulation experiment environment in MATLAB, set the simulation time to 0.4s, and the rated speed of the motor to 1000r/min. The improved sliding mode control scheme is tested, and the results show that the motor output speed, tracking error and electromagnetic torque variation under the improved sliding mode control scheme are smaller than those under the traditional sliding mode control scheme. Under the same simulation conditions, the multi-motor speed synchronization error under the improved sliding mode control scheme is around 0r/min, and its error value is close to 0, so the control effect is higher. In conclusion, the optimization scheme proposed in this study can effectively improve the stability and control accuracy of the multi-motor system.

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Section: Plos Onementioning

confidence: 99%

Research on coupling control of multiple permanent magnet synchronous motors based on NAISMC and SMDO

Hao,

Zhao

2023

PLoS ONE

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“…Chaos is a complex and interesting dynamical phenomenon in nonlinear science. Since Pecora and Carroll demonstrated the feasibility of synchronization of chaotic systems [6], various synchronization methods have been investigated, such as sliding mode control (SMC) [7, 8], observer [9, 10], and finite‐time control [11, 12]. The synchronization of fractional‐order chaotic systems (FOCSs) has received increasing attention due to the presence of chaos in many FO systems and the wide application of chaotic synchronization in engineering [13–15].…”

Section: Introductionmentioning

confidence: 99%

Novel predefined‐time control for fractional‐order systems and its application to chaotic synchronization

Chen,

Zhao,

Xiao

2024

Math Methods in App Sciences

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Based on the fractional calculus and sliding mode control (SMC) techniques, this paper presents a predefined‐time synchronization scheme for fractional‐order chaotic systems (FOCSs). Firstly, a predefined‐time control method is proposed for fractional‐order systems. Subsequently, a novel sliding surface is presented to ensure predefined‐time convergence of the synchronization error. Then, a controller is designed by combining the predefined‐time stability and the SMC method to ensure that the synchronization error converges to zero within the predefined time. Finally, the feasibility and robustness of the scheme are illustrated with two numerical simulation examples.

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“…Second, the synthesized controller is directly implemented in a digital processor. Therefore, control methodologies developed for discrete-time nonlinear systems can be implemented in real systems more effectively (Garrappa and Popolizio, 2011; Shao et al, 2022; Yang et al, 2022; Zhang and Xu, 2019; Zhang et al, 2020; Znidi et al, 2022). A number of processes have a certain regularity; however, they are not completely periodic.…”

Section: Introductionmentioning

confidence: 99%

Exponential convergence in the mean-square sense of nonlocal stochastic almost automorphic genetic regulatory lattice networks

Hao

Zhang

2023

Transactions of the Institute of Measurement and Control

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This paper first establishes the lattice model for nonlocal stochastic genetic regulatory networks with reaction diffusions by employing a mix of the finite difference and Mittag–Leffler time Euler difference techniques. Second, the existence of a unique bounded almost automorphic sequence in distribution and global mean-square exponential convergence to the achieved difference model are investigated. An illustrative example is used to show the feasible of the works of the current paper.

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Discrete indirect adaptive sliding mode control for uncertain Hammerstein nonlinear systems

Cited by 8 publications

References 39 publications

Research on coupling control of multiple permanent magnet synchronous motors based on NAISMC and SMDO

Research on coupling control of multiple permanent magnet synchronous motors based on NAISMC and SMDO

Novel predefined‐time control for fractional‐order systems and its application to chaotic synchronization

Exponential convergence in the mean-square sense of nonlocal stochastic almost automorphic genetic regulatory lattice networks

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