Article
Mathematics, Applied
A. Akbarzadeh Kalat, V. Mokhtari
Summary: The article introduces a new robust adaptive sliding mode controller for uncertain nonlinear systems with only the system output measurable. A robust adaptive fuzzy observer is designed to estimate the system state variables, and a robust adaptive sliding mode controller based on observation states is suggested for achieving stability of the closed-loop system. The proposed technique shows practicality and effectiveness in controlling uncertain nonlinear systems according to simulation results.
IRANIAN JOURNAL OF FUZZY SYSTEMS
(2021)
Article
Mathematics
Bin Li, Jiahao Zhu, Ranran Zhou, Guoxing Wen
Summary: This article proposes a sliding mode control method based on an adaptive neural network for handling nonlinear systems with unknown dynamic functions. By introducing the boundary layer technique and continuous proportional function, the chattering phenomenon caused by discontinuous switching terms is effectively alleviated.
Article
Automation & Control Systems
Majid Moradi Zirkohi
Summary: A hybrid control approach is proposed to control MEMS triaxial gyroscope, combining multiple control techniques to enhance system stability and performance; the method addresses the issues caused by parameter variations, errors, and disturbances, with simulation results confirming the superiority of this approach.
Article
Automation & Control Systems
Hafiz Muhammad Salman Yaseen, Syed Ahmad Siffat, Iftikhar Ahmad, Ali Shafiq Malik
Summary: This paper proposes three nonlinear controllers for position and flux tracking in a magnetic levitation system. Through simulation and comparative analysis, it is found that the adaptive terminal sliding mode control has better performance. The robustness of the proposed controllers is also validated through parameter variations and disturbances.
Article
Computer Science, Information Systems
Xingjian Sun, Lei Zhang, Juping Gu
Summary: In this study, the adaptive sliding mode control (ASMC) strategy is investigated for complex nonlinear systems with matched and unknown nonlinearities and external disturbances. A Gaussian radial basic neural network is used to approximate the nonlinearities and external disturbances. A Takagi-Sugeno (T-S) fuzzy model based integral switching function is introduced to solve the ASMC problem and eliminate the constraint on input gains. The switching control term is represented as a proportional integral (PI) control format to reduce chattering phenomenon and the Lyapunov theory is used to guarantee the stability of the control systems. An experimental simulation is conducted to verify the effectiveness of the proposed sliding mode control (SMC) strategy.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Baopeng Zhu, Yingchun Wang, Huaguang Zhang, Xiangpeng Xie
Summary: This article presents a fuzzy functional observer-based finite-time adaptive sliding-mode control method for nonlinear systems, which reduces conservatism and increases solution space by introducing relaxed matrices and fuzzy Lyapunov functional approach.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Jinhui Zhang, Duanduan Chen, Ganghui Shen, Zhongqi Sun, Yuanqing Xia
Summary: In this paper, disturbance observer based adaptive sliding mode control approaches are proposed for Takagi-Sugeno fuzzy systems with unknown external disturbance. By designing novel dynamic sliding surfaces and adaptive laws, both state- and output-based controllers are designed without input matrix constraints, incorporating disturbance estimates to achieve active disturbance rejection. The effectiveness of the proposed control approaches is demonstrated through numerical examples.
Article
Automation & Control Systems
Behrooz Rahmani, Ali Ziaiefar, Shamsedin Hashemi
Summary: This research explores a model-free control strategy for vibration suppression of base-isolated structures under earthquake excitation. A semi-active base isolated system with a magnetorheological (MR) damper is used, and the displacement of the base isolator is measured by a linear variable differential transformer (LVDT). An adaptive fuzzy sliding mode observer is implemented to estimate the vector of state tracking error, which is then utilized by an adaptive fuzzy sliding mode control scheme to calculate the input voltage of the MR damper. Numerical simulations are conducted to evaluate the effectiveness of the implemented model-free control strategy, highlighting its flexibility and robustness against disturbance rejection and model uncertainty.
Article
Computer Science, Information Systems
Guozhong Yao, Xianxiang Wang, Zhengjiang Wang, Yuhan Xiao
Summary: This paper addresses the problems of sliding mode observer, such as strong parameter dependency, large overshoot, and severe inherent sliding mode chattering, by studying fuzzy control and designing a new type of fuzzy sliding mode observer using a sigmoid function. The new method incorporates adaptive sliding mode gain adjustment and PLL technology for rotor position information. Experimental verification and comparison with traditional sliding mode observer showed that the new fuzzy sliding mode observer can more accurately estimate rotor position and speed, with reduced errors, overshoot, and chattering.
Article
Automation & Control Systems
Jie Wen, Yuanhao Shi, Xiaoqiong Pang, Jianfang Jia, Jianchao Zeng
Summary: In this paper, two state feedback strategies are proposed to exponentially stabilize eigenstates for quantum spin-1/2 systems. The state feedback is improved to increase the real-time state convergence rate and achieve exponential convergence. Global exponential stabilization is achieved with the help of noise-assisted feedback. The state convergence rates of all state feedback strategies are compared, and the superiority of the improved feedback control is verified in numerical simulations.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Engineering, Electrical & Electronic
Gang Chen, Yichen Jiang, Keyi Guo, Liangmo Wang
Summary: This paper proposes a speed tracking method for unmanned driving robot vehicles by adjusting the sliding mode gains using a fuzzy adaptive system. The effectiveness and stability of the proposed method is demonstrated through model establishment and control law derivation.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Mathematics, Interdisciplinary Applications
Yunmei Fang, Siyang Li, Juntao Fei
Summary: In this study, a second-order sliding mode control (SOSMC) with a fractional module using an adaptive fuzzy controller is developed for an active power filter (APF). A second-order sliding surface using a fractional module is designed to reduce discontinuities and chattering, ensuring system stability and simplifying the design process. Additionally, a fuzzy logic control is employed to estimate parameter uncertainties. Simulation and experimental results demonstrate the effectiveness of the designed fractional SOSMC with adaptive fuzzy controller in satisfactorily eliminating harmonics, as well as its good robustness and stability compared to an integer order controller.
FRACTAL AND FRACTIONAL
(2022)
Article
Construction & Building Technology
Abasin Ulasyar, Mostafa K. A. Saleh, Ismail Lazoglu, Yunus Emre Aydogdu
Summary: The article proposes a new vibration control strategy for reduction of vibrations in washing machines using adaptive nonlinear terminal sliding mode control, double coil shear mode magnetorheological dampers, and DC-DC buck converter. The strategy consists of two loops to ensure stable control of current flow, improving washing machine performance. An experimental setup was established to study the performance of the vibration control strategy in comparison with passive dampers and other vibration control techniques reported in literature.
STRUCTURAL CONTROL & HEALTH MONITORING
(2022)
Article
Mathematics
Jesus Alfonso Medrano-Hermosillo, Ricardo Lozoya-Ponce, Abraham Efraim Rodriguez-Mata, Rogelio Baray-Arana
Summary: This paper presents the dynamic modeling and control of robot manipulators using Hamilton's equations in the screw theory framework. The novelty lies in obtaining the laws of control directly with screws and co-screws, which is considered modern robotics by many authors. Geometric algebra (GA) is introduced as a simple and iterative tool to obtain screws and co-screws. The Hamiltonian equations of motion are developed using screws and co-screws, and two control laws are designed for error convergence to zero.
Article
Computer Science, Artificial Intelligence
Esraa Mostafa, Osama Elshazly, Mohammad El-Bardini, Ahmad M. M. El-Nagar
Summary: An adaptive fractional-order sliding mode control (AFOSMC) is proposed for controlling a nonlinear fractional-order system. This control scheme combines sliding mode control and fractional control to improve the response of nonlinear systems. The proposed AFOSMC includes a fractional-order sliding mode control (FOSMC) and a tuning unit that adjusts the parameters of FOSMC using a Takagi-Sugeno-Kang fuzzy logic system. Stability analysis of the proposed controller is carried out using Lyapunov theorem. The practical implementation of AFOSMC using a microcontroller demonstrates improvements and enhancements in controlling a fractional-order gyroscope system.
