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Pitch and yaw motion control of 2 DoF helicopter subjected to faults using sliding-mode control

M. Raghappriya S. Kanthalakshmi
Archives of Control Sciences | 2022 | vol. 32 | No 2 | 359-381 | DOI: 10.24425/acs.2022.141716
Keywords fault tolerant control sliding mode control reaching law super-twisting sensor actuator and component faults
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Abstract

This paper presents a fault-tolerant control scheme for a 2 DOF helicopter. The 2 DOF helicopter is a higher-order multi-input multi-output system featuring non-linearity, cross-coupling, and unstable behaviour. The impact of sensor, actuator, and component faults on such highly complex systems is enormous. This work employs sliding mode control, which is based on reaching and super-twisting laws, to handle the problem of fault control. Simulation tests are carried out to show the effectiveness of the algorithms. Various performance metrics are analyzed and the results show SMC based on super-twisting law provides better control with less chattering. The stability of the closed-loop system is mathematically assured, in the presence of faults, which is a key contribution of this research.
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Authors and Affiliations

M. Raghappriya
1
S. Kanthalakshmi
2
  1. Department of Electronics and Instrumentation Engineering, Government College of Technology, Coimbatore, India
  2. Department of Electrical and Electronics Engineering, PSG College of Technology, Coimbatore, India

High-performance induction motor drive based on adaptive super-twisting sliding mode control approach

Salah Eddine Farhi Djamel Sakri Noureddine Golèa
Archives of Electrical Engineering | 2022 | vol. 71 | No 1 | 245-263 | DOI: 10.24425/aee.2022.140208
Keywords barrier function chattering gains adaptation induction motor drive slidingmode control super twisting
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Abstract

This paper proposes two high-order sliding mode algorithms to achieve highperformance control of induction motor drive. In the first approach, the super-twisting algorithm (STA) is used to reduce the chattering effect and to improve control accuracy. The second approach combines the super-twisting algorithm with a quasi-barrier function technique. While the super-twisting algorithm (STA) aims at the chattering reduction, the Barrier super-twisting algorithm (BSTA) aims to eliminate this phenomenon by providing continuous output control signals. The BSTA is designed to prevent the STA gain from being over-estimated by making these gains to decrease and increase according to system’s uncertainties. Stability and finite-time convergence are guaranteed using Lyapunov’s theory. In addition, the two controlled variables, rotor speed, and rotor flux modulus are estimated based on the second-order sliding mode (SOSM) observer. Finally, simulations are carried out to compare the performance and robustness of two control algorithms without adding the equivalent control. Tests are achieved under external load torque, varying reference speed, and parameter variations.
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Authors and Affiliations

Salah Eddine Farhi
1
Djamel Sakri
1
Noureddine Golèa
1
  1. Laboratory of Electrical Engineering and Automatic, LGEA, Larbi Ben M’hidi University, Oum El Bouaghi, Algeria

Robust hybrid synchronization control of chaotic 3-cell CNN with uncertain parameters using smooth super twisting algorithm

Nazam Siddique Fazal ur Rehman Uzair Raoof Shahid Iqbal Muhammad Rashad
Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 5 | e146474 | DOI: 10.24425/bpasts.2023.146474
Keywords hybrid synchronization cellular neural network sliding mode control smooth super twisting algorithm Lyapunov stability theory
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Abstract

This paper presents the control design framework for the hybrid synchronization (HS) and parameter identification of the 3-Cell Cellular Neural Network. The cellular neural network (CNN) of this kind has increasing practical importance but due to its strong chaotic behavior and the presence of uncertain parameters make it difficult to design a smooth control framework. Sliding mode control (SMC) is very helpful for this kind of environment where the systems are nonlinear and have uncertain parameters and bounded disturbances. However, conventional SMC offers a dangerous chattering phenomenon, which is not acceptable in this scenario. To get chattering-free control, smooth higher-order SMC formulated on the smooth super twisting algorithm (SSTA) is proposed in this article. The stability of the sliding surface is ensured by the Lyapunov stability theory. The convergence of the error system to zero yields hybrid synchronization and the unknown parameters are computed adaptively. Finally, the results of the proposed control technique are compared with the adaptive integral sliding mode control (AISMC). Numerical simulation results validate the performance of the proposed algorithm.
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Authors and Affiliations

Nazam Siddique
1
ORCID: ORCID
Fazal ur Rehman
2
Uzair Raoof
3
Shahid Iqbal
1
Muhammad Rashad
3
  1. University of Gujrat, Gujrat, Pakistan
  2. Capital University of Science and Technology, Islamabad, Pakistan
  3. University of Lahore, Lahore, Pakistan

Robust estimation based nonlinear higher order sliding mode control strategies for PMSG-WECS

Awais Nazir Safdar Abbas Khan Malak Adnan Khan Zaheer Alam Imran Khan Muhammad Irfan Saifur Rehman Grzegorz Nowakowski
Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 5 | e147063 | DOI: 10.24425/bpasts.2023.147063
Keywords WECS robust control MPPT back-stepping SMC super-twisting algorithm (STA) high gain observer ANN function fitting
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Abstract

The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP). This research paper addresses a sophisticated MPP tracking (MPPT) strategy to ensure optimum (maximum) power out of the WECS despite environmental (wind) variations. This study considers a WECS (fixed pitch, 3KW, variable speed) coupled with a permanent magnet synchronous generator (PMSG) and proposes three sliding mode control (SMC) based MPPT schemes, a conventional first order SMC (FOSMC), an integral back-stepping-based SMC (IBSMC) and a super-twisting reachability-based SMC, for maximizing the power output. However, the efficacy of MPPT/control schemes rely on availability of system parameters especially, uncertain/nonlinear dynamics and aerodynamic terms, which are not commonly accessible in practice. As a remedy, an off-line artificial function-fitting neural network (ANN) based on Levenberg-Marquardt algorithm is employed to enhance the performance and robustness of MPPT/control scheme by effectively imitating the uncertain/nonlinear drift terms in the control input pathways. Furthermore, the speed and missing derivative of a generator shaft are determined using a high-gain observer (HGO). Finally, a comparison is made among the stated strategies subjected to stochastic and deterministic wind speed profiles. Extensive MATLAB/Simulink simulations assess the effectiveness of the suggested approaches.
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Authors and Affiliations

Awais Nazir
1
Safdar Abbas Khan
1
Malak Adnan Khan
2
Zaheer Alam
3
Imran Khan
4
Muhammad Irfan
5
ORCID: ORCID
Saifur Rehman
5
Grzegorz Nowakowski
6
ORCID: ORCID
  1. Department of Electrical Engineering, National University of Science and Technology, Pakistan
  2. Department of Electronics Engineering, University of Engineering and Technology Peshawar, Abbottabad campus, Pakistan
  3. Department of Electrical and Computer Engineering, COMSATS University Islamabad, Abbottabad Campus, Pakistan
  4. Department of Electrical, Electronics and Computer Systems, College of Engineering and Technology, University of Sargodha, Pakistan
  5. Electrical Engineering Department, College of Engineering, Najran University, Saudi Arabia
  6. Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Cracow, Poland

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