Article
Computer Science, Information Systems
Mohammed Yousri Silaa, Oscar Barambones, Aissa Bencherif
Summary: This paper presents an adaptive PID control algorithm using stochastic gradient descent with momentum (SGDM) for a proton exchange membrane fuel cell (PEMFC) power system. By minimizing the cost function and adapting the PID parameters according to perturbation changes, this method achieves fast convergence and high robustness in control performance.
Article
Computer Science, Artificial Intelligence
Ahmad M. El-Nagar, Mohammad El-Bardini, A. Aziz Khater
Summary: This study presents a general type-2 Takagi-Sugeno-Kang fuzzy controller (GT2-TSKFC) for controlling uncertain systems. The proposed controller utilizes equidistant type-2 triangular membership functions (MFs) for the antecedents, Larsen's implication method, type-1 fuzzy sets for the consequent parameters, and a direct defuzzification method. The adaptation of alpha-plane and apex of the secondary MFs is performed using the Lyapunov function to ensure the stability of the controlled system. Experimental results demonstrate the robustness and effectiveness of the proposed scheme compared to other fuzzy controllers.
APPLIED SOFT COMPUTING
(2023)
Article
Mathematics, Interdisciplinary Applications
S. Hadipour Lakmesari, M. J. Mahmoodabadi, M. Yousef Ibrahim
Summary: This paper presents an adaptive robust control algorithm based on fuzzy rules and gradient descent laws, which combines reliable feedback linearization approach with robust sliding mode controller to design a stable control effort for an under-actuated nonlinear inverted pendulum system. The analysis and results on the inverted pendulum system demonstrate the desired performance of the proposed control scheme by providing optimal smooth control input, suitable tracking performance, and proper time responses.
CHAOS SOLITONS & FRACTALS
(2021)
Correction
Optics
Manabu Arikawa, Kazunori Hayashi
Summary: This erratum corrects errors in Fig. 9(b) and Fig. 14 of our published paper [Opt. Express 31, 13104 (2023)]. Other results, descriptions, and conclusions are not affected by this correction.
Article
Computer Science, Artificial Intelligence
Kaushik Das Sharma, Amitava Chatterjee, Patrick Siarry, Anjan Rakshit
Summary: This paper proposes a unique design of direct stable adaptive fuzzy logic controllers for non-linear systems with large and fast disturbances, utilizing a hybrid approach of local adaptation and global optimization. The controllers aim to optimize structure and parameters for stability, tracking performance, and disturbance rejection, using the nature of disturbances in the design process. Implementation in benchmark case studies shows the controllers' effectiveness.
Article
Engineering, Marine
Feng Lyu, Xin Xu, Xin Zha
Summary: An adaptive gradient descent algorithm (AGDA) based on a fuzzy system is proposed to improve the attitude estimation accuracy and adaptability of unmanned underwater vehicles (UUVs) under various ocean environments. The algorithm predicts the quaternion using gyroscope data, calibrates accelerometer data based on the predicted quaternion, and utilizes a fuzzy system generated by genetic algorithm to solve the adaptive coefficient. The algorithm achieves data fusion using gradient descent to compensate for the accumulated error of the gyroscope.
Article
Automation & Control Systems
Xuebo Yang, Xiaolong Zheng
Summary: This paper proposes a novel control scheme for position tracking control of an induction motor with completely unknown nonlinearities, utilizing the gradient descent algorithm, adaptive backstepping technique, neural networks, and extended differentiators. The proposed control strategy shows advantages over direct adaptive NN control strategies in simulation examples by providing training for all parameters of NNs and ensuring convergence of both NN approximation error and system tracking error with the help of the gradient descent algorithm and Lyapunov stability criterion.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Information Systems
Samir Zeghlache, Loutfi Benyettou, Ali Djerioui, Mohammed Zinelaabidine Ghellab
Summary: This article presents an adaptive fuzzy control method for stabilizing the twin rotor multi-input multi-output system and achieving precise tracking and reference position control. Experimental implementation demonstrates the capability of the developed control algorithm.
IEEE SYSTEMS JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Seyyed Morteza Ghamari, Fatemeh Khavari, Hasan Mollaee
Summary: In this paper, a Lyapunov-based model reference PID control strategy is proposed for a DC/DC Buck converter. The PID strategy is enhanced with a Lyapunov definition-based adaptive mechanism to increase stability and robustness under various disturbances. The system is treated as a black-box, eliminating the need for accurate mathematical modeling and reducing computational burden. The Lyapunov concept offers faster and more accurate optimization with reliable stability assurance. Simulation and experimental results confirm the superior performance of the Lyapunov-based PID strategy compared to conventional FOPID and PID control techniques.
Article
Engineering, Marine
Enver Tatlicioglu, Bayram Melih Yilmaz, Aydogan Savran, Musa Alci
Summary: This article focuses on the tracking control of surface vessels with uncertainties in the dynamical model. A model independent strategy is used, where the dynamical uncertainties are modeled using a fuzzy logic network. The controller design includes proportional derivative feedback and self-adjusting fuzzy logic compensation. Stability analysis based on Lyapunov method is performed to ensure semi-global practical tracking. Numerical simulations demonstrate the effectiveness of the proposed method.
Article
Automation & Control Systems
Mingjun Dai, Zelong Zhang, Xiong Lai, Xiaohui Lin, Hui Wang
Summary: Due to the issues with SGD optimization algorithms, the Adam algorithm, although it can adaptively adjust the update direction and learning rate, still suffers from overshoot phenomenon and slow convergence. In this study, the concept of PID controller is borrowed to propose a complete adaptive PID optimizer, which successfully alleviates the overshoot phenomenon and speeds up the convergence.
IET CONTROL THEORY AND APPLICATIONS
(2023)
Article
Automation & Control Systems
Gopisetti Srinivasarao, Arun K. Samantaray, Sanjoy K. Ghoshal
Summary: This work presents a bond graph (BG) model and a robust cascaded controller for a twin-rotor system (TRS). The proposed controller is robust against un-modeled dynamics and external disturbances, and it performs better in terms of trajectory tracking error and disturbance rejection compared to existing controllers for the TRS.
Article
Chemistry, Analytical
Farzin Piltan, Jong-Myon Kim
Summary: The research aims to design an adaptive digital twin algorithm for fault diagnosis and crack size identification in bearings, using a combination of mathematical and data-driven techniques to improve reliability and accuracy. The proposed technique involves modeling and estimating signals, with the use of adaptive observer and support vector machine for fault diagnosis and crack size identification. Testing on the Case Western Reserve University Bearing Dataset showed high average detection accuracies for fault diagnosis and crack size identification.
Article
Computer Science, Artificial Intelligence
Liu Yang, Deng Cai
Summary: Adaptive gradient learning methods like Adam, RMSProp, and AdaGrad are crucial for training deep neural networks, but they may face convergence and generalization issues. AdaDB introduces a data-dependent learning rate upper bound solution and has been theoretically proven to converge in non-convex settings.
Article
Automation & Control Systems
Abigail Maria Elena Ramirez Mendoza, Wen Yu
Summary: This article introduces a fuzzy adaptive control law (FACL) for trajectory tracking of a small-scale UAV using a new fuzzy adaptive neural proportional integral derivative (FANPID) controller. The FACL uses the adaptivity of the FANPID-Lyapunov controller to estimate rotation angles when a reference trajectory is provided. The UAV parameters are identified using the fuzzy adaptive neurons (FAN) method and experimental aerodynamic data. The FANPID-Lyapunov controller optimizes trajectory tracking and stability analysis is performed. Simulation results in Matlab (R)/Simulink show the effectiveness, adaptivity, and optimization of the flight control system, reducing error considerably compared to other controllers.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Automation & Control Systems
Mohsen Sadeghi, Mohammad Farrokhi
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2019)
Article
Automation & Control Systems
Mohammad-Reza Rahmani, Mohammad Farrokhi
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2019)
Article
Automation & Control Systems
Mohammad-Reza Rahmani, Mohammad Farrokhi
Article
Automation & Control Systems
Surena Rad-Moghadam, Mohammad Farrokhi
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2020)
Article
Automation & Control Systems
Reza Heydari, Mohammad Farrokhi
Summary: This paper presents a robust tube-based model predictive control method for polytopic linear parameter varying systems subject to bounded additive disturbances, utilizing the notion of polar dual set and maximizing the shape and size of the additive disturbance set online. Numerical simulation demonstrates the efficacy of the proposed approach.
Article
Computer Science, Artificial Intelligence
Farzaneh Sabbaghian-Bidgoli, Mohammad Farrokhi
Summary: This paper studies sensor and actuator Fault-Tolerant Control (FTC) of nonlinear systems, proposing a Polynomial Fuzzy Unknown Input Observer (PFUIO) for estimating system states and faults. The proposed approach shows better performance compared with the Linear Matrix Inequality (LMI) approach.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Farzaneh Sabbghian-Bidgoli, Mohammad Farrokhi
Summary: This article studies the integrated fault-tolerant control and fault estimation problem using the polynomial fuzzy model based on the sum of squares approach. It designs a polynomial fuzzy observer to estimate time-varying faults and reduces the dimensions of the problem. The proposed approach outperforms the linear matrix inequality approach in fault-tolerant and fault estimation performance.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Reza Heydari, Mohammad Farrokhi
Summary: This paper addresses the problem of designing robust event-triggered tube-based model predictive control (TMPC) for constrained linear parameter-varying systems. The proposed method introduces a novel modification of homothetic TMPC to consider the effect of open-loop control between triggering times, and derives the triggering condition based on the input-to-state stability (ISS) concept to reduce communication traffic. The simulation results demonstrate the effectiveness of the proposed scheme while reducing the update frequency.
SYSTEMS & CONTROL LETTERS
(2022)
Article
Automation & Control Systems
Farzaneh Sabbaghian-Bidgoli, Mohammad Farrokhi
Summary: This paper proposes a method for robust observer-based Integrated Fault-Tolerant Control (IFTC) using a homogeneous polynomial Lyapunov function (HPLF) in nonlinear systems modeled by the polynomial fuzzy model (PFM). By avoiding the appearance of non-convex terms and solving the control conditions with polynomial matrix inequalities, less conservative control results are obtained. The use of a non-quadratic Lyapunov function in designing a polynomial fuzzy unknown-input observer enables better estimation of system states and actuator faults.
IET CONTROL THEORY AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Hamid Toshani, Mohammad Farrokhi
Summary: This paper proposes a strategy combining optimal discrete-time sliding-mode control and recurrent neural networks for a class of uncertain discrete-time linear systems. The dynamic and algebraic model of the neural network is derived based on the optimization conditions of the quadratic problem and their relationship with the projection theory. The convergence of the neural network is analyzed using the Lyapunov stability theory, and a singular value-based analysis is employed for robustness evaluation.
Article
Automation & Control Systems
Surena Rad-Moghadam, Mohammad Farrokhi
Summary: This paper proposes a near-optimal controller design for constrained nonlinear affine systems using a Recurrent Neural Network (RNN) and Extended State Observers (ESOs). The proposed method can handle output constraints by employing the Control Barrier Function (CBF). It aims to achieve a near-optimal performance within the constraints. The effectiveness of the proposed method is illustrated through a simulating example of a two-inverted pendulums system.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2023)
Article
Computer Science, Information Systems
Sina Naderian, Mohammad Farrokhi
Summary: This paper proposes an Adaptive Back-stepping Data-Driven Terminal Sliding Mode Controller (ABDTSMC) for non-affine MIMO systems. The proposed controller reduces dependence on the mathematical model and eliminates chattering phenomenon. It utilizes a Disturbance Observer (DOB) based on neural network to estimate uncertainties and disturbances.
Article
Engineering, Multidisciplinary
Melika Ataollahi, Mohammad Farrokhi
Summary: This article proposes an improved Q-learning method and an adaptive artificial potential field method for online path planning in unknown environments with obstacles. The improved Q-learning accelerates the learning process and overcomes local minima, while the adaptive artificial potential field method allows for proper navigation of mobile robots. The proposed method guarantees target tracking, collision avoidance, and optimal path planning.
JOURNAL OF ENGINEERING-JOE
(2023)
Article
Robotics
Shabnam Shakourzadeh, Mohammad Farrokhi
INTELLIGENT SERVICE ROBOTICS
(2020)
Article
Automation & Control Systems
Bahareh Vatankhah, Mohammad Farrokhi
ASIAN JOURNAL OF CONTROL
(2019)
