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Journal articles on the topic 'Classical adaptive controllers'

Author: Grafiati

Published: 6 September 2023

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1

Costa, Victor, and Wesley Beccaro. "Benefits of Intelligent Fuzzy Controllers in Comparison to Classical Methods for Adaptive Optics." Photonics 10, no. 9 (2023): 988. http://dx.doi.org/10.3390/photonics10090988.

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Adaptive Optics (AO) systems have been developed throughout recent decades as a strategy to compensate for the effects of atmospheric turbulence, primarily caused by poor astronomical seeing. These systems reduce the wavefront distortions using deformable mirrors. Several AO simulation tools have been developed, such as the Object-Oriented, MATLAB, and Adaptive Optics Toolbox (OOMAO), to assist in the project of AO. However, the main AO simulators focus on AO models, not prioritizing the different control techniques. Moreover, the commonly applied control strategies in ground-based telescopes

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Intidam, Abdessamad, Hassan El Fadil, Halima Housny, et al. "Development and Experimental Implementation of Optimized PI-ANFIS Controller for Speed Control of a Brushless DC Motor in Fuel Cell Electric Vehicles." Energies 16, no. 11 (2023): 4395. http://dx.doi.org/10.3390/en16114395.

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This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is a classical proportional integral (PI) controller. In contrast, the second one is based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive neuro-fuzzy inference system (PI-ANFIS) and particle swarm optimization-proportional integral-adaptive neuro-fuzzy inference system (PSO-PI-ANFIS)). The control objective is to regulate the rotor speed to its desired reference value in the presence of load torque disturbance and parameter

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3

Kamal, Tariq, Murat Karabacak, Vedran S. Perić, Syed Zulqadar Hassan, and Luis M. Fernández-Ramírez. "Novel Improved Adaptive Neuro-Fuzzy Control of Inverter and Supervisory Energy Management System of a Microgrid." Energies 13, no. 18 (2020): 4721. http://dx.doi.org/10.3390/en13184721.

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In this paper, energy management and control of a microgrid is developed through supervisor and adaptive neuro-fuzzy wavelet-based control controllers considering real weather patterns and load variations. The supervisory control is applied to the entire microgrid using lower–top level arrangements. The top-level generates the control signals considering the weather data patterns and load conditions, while the lower level controls the energy sources and power converters. The adaptive neuro-fuzzy wavelet-based controller is applied to the inverter. The new proposed wavelet-based controller impr

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Zhang, Chao, Sheng Xiu Zhang, and Yi Nan Liu. "Invariant Manifolds Based Modular Adaptive Control for a Class of Nonlinear Systems with Application to Flight Control." Applied Mechanics and Materials 373-375 (August 2013): 1488–92. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1488.

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In this paper a novel modular framework for adaptive control for a class of nonlinear system is developed and applied to flight controller design. The framework is based on the invariant manifolds approach with a new type of reduced-order estimator which allows for stable dynamics to be assigned to the estimation error. We show that this method can be applied to systems with unknown parameters, leading to a new class of modular adaptive controllers which is easier to tune compared to controllers obtained using the classical adaptive approaches and does not suffer from unpredictable dynamical b

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Humaidi, Amjad J., Ibraheem Kasim Ibraheem, Ahmad Taher Azar, and Musaab E. Sadiq. "A New Adaptive Synergetic Control Design for Single Link Robot Arm Actuated by Pneumatic Muscles." Entropy 22, no. 7 (2020): 723. http://dx.doi.org/10.3390/e22070723.

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This paper suggests a new control design based on the concept of Synergetic Control theory for controlling a one-link robot arm actuated by Pneumatic artificial muscles (PAMs) in opposing bicep/tricep positions. The synergetic control design is first established based on known system parameters. However, in real PAM-actuated systems, the uncertainties are inherited features in their parameters and hence an adaptive synergetic control algorithm is proposed and synthesized for a PAM-actuated robot arm subjected to perturbation in its parameters. The adaptive synergetic laws are developed to esti

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Noordin, Aminurrashid, Mohd Ariffanan Mohd Basri, and Zaharuddin Mohamed. "Real-Time Implementation of an Adaptive PID Controller for the Quadrotor MAV Embedded Flight Control System." Aerospace 10, no. 1 (2023): 59. http://dx.doi.org/10.3390/aerospace10010059.

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This paper presents the real-time implementation of an altitude-embedded flight controller using proportional, integral, and derivative (PID) control, adaptive PID (APID) control, and adaptive PID control with a fuzzy compensator (APIDFC) for a micro air vehicle (MAV), specifically, for a Parrot Mambo Minidrone. In order to obtain robustness against disturbance, the adaptive mechanism, which was centered on the second-order sliding mode control, was applied to tune the classical parameters of the PID controller of the altitude controller. Additionally, a fuzzy compensator was introduced to dim

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Braz-César, Manuel, and Rui Barros. "Optimization of a Fuzzy Logic Controller for MR Dampers Using an Adaptive Neuro-Fuzzy Procedure." International Journal of Structural Stability and Dynamics 17, no. 05 (2016): 1740007. http://dx.doi.org/10.1142/s0219455417400077.

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Intelligent and adaptive control systems are naturally suitable to deal with dynamic uncertain systems with non-smooth nonlinearities; they constitute an important advantage over conventional control approaches. This control technology can be used to design powerful and robust controllers for complex vibration engineering problems such as vibration control of civil structures. Fuzzy logic based controllers are simple and robust systems that are rapidly becoming a viable alternative for classical controllers. Furthermore, new control devices such as magnetorheological (MR) dampers have been wid

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Zhu, Gao Ke, Xiao Gang Duan, and Hua Deng. "Adaptive Fuzzy PID Force Control for a Prosthetic Hand." Applied Mechanics and Materials 433-435 (October 2013): 93–101. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.93.

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An adaptive fuzzy proportional-integral-derivative (PID) force control strategy for a prosthetic hand is presented. The classical PID controller is also applied on the prosthetic hand as comparison. The parameters of PID controller are firstly tuned by Cut and Try method. Then a fuzzy logic system is used to adjust those parameters on line. Real-time force control experiments are realized on LabVIEW and PXI (PCI eXtensions for Instrumentation) real-time (RT) platforms. A rigid object and a compliant object are grasped by the prosthesis respectively to test the performance of controllers. Exper

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Mahdi, Shaymaa M., Noor Q. Yousif, Ahmed A. Oglah, Musaab E. Sadiq, Amjad J. Humaidi, and Ahmad Taher Azar. "Adaptive Synergetic Motion Control for Wearable Knee-Assistive System: A Rehabilitation of Disabled Patients." Actuators 11, no. 7 (2022): 176. http://dx.doi.org/10.3390/act11070176.

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In this study, synergetic-based adaptive control design is developed for trajectory tracking control of joint position in knee-rehabilitation system. This system is often utilized for rehabilitation of patients with lower-limb disabilities. However, this knee-assistive system is subject to uncertainties when applied to different persons undertaking exercises. This is due to the different masses and inertias of different persons. In order to cope with these uncertainties, an adaptive scheme has been proposed. In this study, an adaptive synergetic control scheme is established, and control laws

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10

Uçak, Kemal, and Beyza Nur Arslantürk. "Adaptive MIMO fuzzy PID controller based on peak observer." An International Journal of Optimization and Control: Theories & Applications (IJOCTA) 13, no. 2 (2023): 139–50. http://dx.doi.org/10.11121/ijocta.2023.1247.

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In this paper, a novel peak observer based adaptive multi-input multi-output (MIMO) fuzzy proportional-integral-derivative (PID) controller has been introduced for MIMO time delay systems. The adaptation mechanism proposed by Qiao and Mizumoto [1] for single-input single-output (SISO) systems has been enhanced for MIMO system adaptive control. The tracking, stabilization and disturbance rejection performances of the proposed adaptation mechanism have been evaluated for MIMO systems by comparing with non-adaptive fuzzy PID and classical PID controllers. The obtained results indicate that the in

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Portillo, Patricia, Luis E. Garza-Castañón, Luis I. Minchala-Avila, Adriana Vargas-Martínez, Vicenç Puig Cayuela, and Pierre Payeur. "Robust Nonlinear Trajectory Controllers for a Single-Rotor UAV with Particle Swarm Optimization Tuning." Machines 11, no. 9 (2023): 870. http://dx.doi.org/10.3390/machines11090870.

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This paper presents the utilization of robust nonlinear control schemes for a single-rotor unmanned aerial vehicle (SR-UAV) mathematical model. The nonlinear dynamics of the vehicle are modeled according to the translational and rotational motions. The general structure is based on a translation controller connected in cascade with a P-PI attitude controller. Three different control approaches (classical PID, Super Twisting, and Adaptive Sliding Mode) are compared for the translation control. The parameters of such controllers are hard to tune by using a trial-and-error procedure, so we use an

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Lou, Ya’nan, Haoyu Lin, Pengkun Quan, Dongbo Wei, and Shichun Di. "Robust Adaptive Control of Fully Constrained Cable-Driven Serial Manipulator with Multi-Segment Cables Using Cable Tension Sensor Measurements." Sensors 21, no. 5 (2021): 1623. http://dx.doi.org/10.3390/s21051623.

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The structure of the cable-driven serial manipulator (CDSM) is more complex than that of the cable-driven parallel manipulator (CDPM), resulting in higher model complexity and stronger structural and parametric uncertainties. These drawbacks challenge the stable trajectory-tracking control of a CDSM. To circumvent these drawbacks, this paper proposes a robust adaptive controller for an n-degree-of-freedom (DOF) CDSM actuated by m cables. First, two high-level controllers are designed to track the joint trajectory under two scenarios, namely known and unknown upper bounds of uncertainties. The

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Yue, Wei Qiang, Li Qiang Jin, and Chuan Xue Song. "An Auto-Adaptive GA-PID Control Method Based on CMAC Net." Advanced Materials Research 219-220 (March 2011): 1139–44. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.1139.

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This paper aimed at solving the difficulty of nonlinear process control by classical PID controller. The author structured a GA-PID controller taking advantage of the multipoint optimizing and fast compute speed of GA, which can get the optimal PID parameters by on-line turning. At the same time, the author introduced a CMAC feed-forward controller which make full use of the high precision to approach nonlinearly object of CMAC. Combine them, a concurrent pattern control method appear, which synthesize advantages of two controllers and is more fit for nonlinear process. The simulation result i

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Kadjoudj, Mohamed, Noureddine Golea, and Hachemi Benbouzid. "Fuzzy rule: Based model reference adaptive control for PMSM drives." Serbian Journal of Electrical Engineering 4, no. 1 (2007): 13–22. http://dx.doi.org/10.2298/sjee0701013k.

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The objective of the model reference adaptive fuzzy control (MRAFC) is to change the rules definition in the direct fuzzy logic controller (FLC) and rule base table according to the comparison between the reference model output signal and system output. The MRAFC is composed by the fuzzy inverse model and a knowledge base modifier. Because of its improved algorithm, the MRAFC has fast learning features and good tracking characteristics even under severe variations of system parameters. The learning mechanism observes the plant outputs and adjusts the rules in a direct fuzzy controller, so that

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15

Maalej, Boutheina, Rim Jallouli Khlif, Chokri Mhiri, Mohamed Habib Elleuch, and Nabil Derbel. "L 1 Adaptive Fractional Control Optimized by Genetic Algorithms with Application to Polyarticulated Robotic Systems." Mathematical Problems in Engineering 2021 (April 9, 2021): 1–14. http://dx.doi.org/10.1155/2021/5579541.

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Recently, an adaptive control approach has been proposed. This approach, named L 1 adaptive control, involves the insertion of a low-pass filter at the input of the Model Reference Adaptive Control (MRAC). This controller has been designed to overcome several limitations of classical adaptive controllers such as (i) the initialization of estimated parameters, (ii) the stability problems with high adaptation gains, and (iii) the appropriate parameter excitation. In this paper, a new design of the filter is presented, used for L 1 adaptive control, for which the desired performances are guarante

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Abut, Tayfun, and Servet Soyguder. "Real-time control and application with self-tuning PID-type fuzzy adaptive controller of an inverted pendulum." Industrial Robot: the international journal of robotics research and application 46, no. 1 (2019): 159–70. http://dx.doi.org/10.1108/ir-10-2018-0206.

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PurposeThis paper aims to keep the pendulum on the linear moving car vertically balanced and to bring the car to the equilibrium position with the designed controllers.Design/methodology/approachAs inverted pendulum systems are structurally unstable and nonlinear dynamic systems, they are important mechanisms used in engineering and technological developments to apply control techniques on these systems and to develop control algorithms, thus ensuring that the controllers designed for real-time balancing of these systems have certain performance criteria and the selection of each controller me

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17

Guan, Wei, Haowen Peng, Xianku Zhang, and Hui Sun. "Ship Steering Adaptive CGS Control Based on EKF Identification Method." Journal of Marine Science and Engineering 10, no. 2 (2022): 294. http://dx.doi.org/10.3390/jmse10020294.

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In recent years, marine autonomous surface vessels (MASS) have grown into a ship research issue to increase the level of autonomy of ship behavior decision-making and control while sailing at sea. This paper focuses on the MASS motion control module design that aims to improve the accuracy and reliability of ship steering control systems. Nevertheless, the stochastic sea and wind environment have led to the extensive use of filters and state observers for estimating the ship-motion-related parameters, which are important for ship steering control systems. In particular, the ship maneuverabilit

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18

Timene, Aristide, Ndjiya Ngasop, and Haman Djalo. "Tractor-Implement Tillage Depth Control Using Adaptive Neuro-Fuzzy Inference System (ANFIS)." Proceedings of Engineering and Technology Innovation 19 (May 25, 2021): 53–61. http://dx.doi.org/10.46604/peti.2021.7522.

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This study presents a design of an adaptive neuro-fuzzy controller for tractors’ tillage operations. Since the classical controllers allows plowing depth errors due to the variations of lands structure, the use of the combined neural networks and fuzzy logic methods decreases these errors. The proposed controller is based on Adaptive Neuro-Fuzzy Inference System (ANFIS), which permits the generation of fuzzy rules to cancel the nonlinearity and disturbances on the implement. The design and simulations of the system, which consist of a hitch-implement mechanism, an electro-hydraulic actuator, a

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Al-Dujaili, Ayad Q., Amjad J. Humaidi, Ziyad T. Allawi, and Musaab E. Sadiq. "Earthquake Hazard Mitigation for Uncertain Building Systems Based on Adaptive Synergetic Control." Applied System Innovation 6, no. 2 (2023): 34. http://dx.doi.org/10.3390/asi6020034.

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This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controll

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Suarez-Rivera, Guiovanny, Nelson David Muñoz-Ceballos, and Henry Mauricio Vásquez-Carvajal. "Development of an Adaptive Trajectory Tracking Control of Wheeled Mobile Robot." Revista Facultad de Ingeniería 30, no. 55 (2021): e12022. http://dx.doi.org/10.19053/01211129.v30.n55.2021.12022.

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Classical modeling and control methods applied to differential locomotion mobile robots generate mathematical equations that approximate the dynamics of the system and work relatively well when the system is linear in a specific range. However, they may have low accuracy when there are many variations of the dynamics over time or disturbances occur. To solve this problem, we used a recursive least squares (RLS) method that uses a discrete-time structure first-order autoregressive model with exogenous variable (ARX). We design and modify PID adaptive self-adjusting controllers in phase margin a

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Dmitrii, Shprekher, Babokin Gennadii, Kolesnikov Evgenii, and Zelenkov Aleksandr. "Rating the speed of the shearer’s electric motor drive load automatic control." Izvestiya vysshikh uchebnykh zavedenii Gornyi zhurnal, no. 6 (September 24, 2020): 109–20. http://dx.doi.org/10.21440/0536-1028-2020-6-109-120.

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Introduction. It is possible to improve productivity, effectiveness, and cost-efficiency of coal extraction due to the efficient use of physical resources, technical upgrade of mechanized longwall equipment, and introduction of advanced technologies and control methods. The existing method of shearer electric motor drive automation based on the automated load controller of Uran type has a significant drawback of low speed. In case the actuator (A) meets solid rock and the shearer’s (S) speed is not changed, it may result in heavy shock loads on A and its transmission, therefore, increased wear

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Tárník, Marián, and Ján Murgaš. "Model Reference Adaptive Control of Permanent Magnet Synchronous Motor." Journal of Electrical Engineering 62, no. 3 (2011): 117–25. http://dx.doi.org/10.2478/v10187-011-0020-4.

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Model Reference Adaptive Control of Permanent Magnet Synchronous MotorIn this paper the classical theory of the direct Model Reference Adaptive Control is used to develop a control algorithm for Permanent Magnet Synchronous Motor (PMSM). A PMSM model widely used in electric drives community is considered as base for control system development. Conventionally used controllers are replaced by adaptive ones. The resulting control system adapts to changes in any of PMSM parameters.

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Younesi, Abdollah, Hossein Shayeghi, and Pierluigi Siano. "Assessing the Use of Reinforcement Learning for Integrated Voltage/Frequency Control in AC Microgrids." Energies 13, no. 5 (2020): 1250. http://dx.doi.org/10.3390/en13051250.

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The main purpose of this paper is to present a novel algorithmic reinforcement learning (RL) method for damping the voltage and frequency oscillations in a micro-grid (MG) with penetration of wind turbine generators (WTG). First, the continuous-time environment of the system is discretized to a definite number of states to form the Markov decision process (MDP). To solve the modeled discrete RL-based problem, Q-learning method, which is a model-free and simple iterative solution mechanism is used. Therefore, the presented control strategy is adaptive and it is suitable for the realistic power

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Ladaci, Samir, Abdelfatah Charef, and Jean Loiseau. "Robust Fractional Adaptive Control Based on the Strictly Positive Realness Condition." International Journal of Applied Mathematics and Computer Science 19, no. 1 (2009): 69–76. http://dx.doi.org/10.2478/v10006-009-0006-6.

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Robust Fractional Adaptive Control Based on the Strictly Positive Realness ConditionThis paper presents a new approach to robust adaptive control, using fractional order systems as parallel feedforward in the adaptation loop. The problem is that adaptive control systems may diverge when confronted with finite sensor and actuator dynamics, or with parasitic disturbances. One of the classical robust adaptive control solutions to these problems makes use of parallel feedforward and simplified adaptive controllers based on the concept of positive realness. The proposed control scheme is based on t

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Timis, Daniel D., Cristina I. Muresan, and Eva-H. Dulf. "Design and Experimental Results of an Adaptive Fractional-Order Controller for a Quadrotor." Fractal and Fractional 6, no. 4 (2022): 204. http://dx.doi.org/10.3390/fractalfract6040204.

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The use of multi-copter systems started to grow over the last years in various applications. The designed solutions require high stability and maneuverability. To fulfill these specifications, a robust control strategy must be designed and integrated. Focusing on this challenge, this research proposes an adaptive control design applied to a physical model of a quadrotor prototype. The proposed adaptive structure guarantees robustness, control flexibility, and stability to the whole process. The prototype components, structure, and laboratory testing equipment that are used to run the experimen

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Modirrousta, Alireza, and Mahdi Khodabandeh. "Adaptive non-singular terminal sliding mode controller: new design for full control of the quadrotor with external disturbances." Transactions of the Institute of Measurement and Control 39, no. 3 (2016): 371–83. http://dx.doi.org/10.1177/0142331215611210.

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This paper proposes two different adaptive robust sliding mode controllers for attitude, altitude and position control of a quadrotor. Firstly, it proposes a backstepping non-singular terminal sliding mode control with an adaptive algorithm that is applied to the quadrotor for free chattering, finite time convergence and robust aims. In this control scheme instead of regular control input, the derivative of the control input is achieved from a non-singular terminal second-layer sliding surface. An adaptive tuning method is utilized to deal with the external disturbances whose upper bounds are

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Eissa, M. Abdullah. "Novel Fuzzy-Based Self-Adaptive Single Neuron PID Load Frequency Controller for Power System." Power Electronics and Drives 4, no. 1 (2019): 141–50. http://dx.doi.org/10.2478/pead-2019-0002.

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AbstractThis paper proposes a newly adaptive single-neuron proportional integral derivative (SNPID) controller that uses fuzzy logic as an adaptive system. The main problem of the classical controller is lacking the required robustness against disturbers, measurement noise in industrial applications. The new formula of the proposed controller helps in fixing this problem based on the fuzzy logic technique. In addition, the genetic algorithm (GA) is used to optimize parameters of the SNPID controller. Because of the high demands on the availability and efficiency of electrical power production,

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Aljuboury, Anwer S., Akram Hashim Hameed, Ahmed R. Ajel, Amjad J. Humaidi, Ahmed Alkhayyat, and Ammar K. Al Mhdawi. "Robust Adaptive Control of Knee Exoskeleton-Assistant System Based on Nonlinear Disturbance Observer." Actuators 11, no. 3 (2022): 78. http://dx.doi.org/10.3390/act11030078.

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This study presents a control design of an angular position for the exoskeleton knee assistance system based on a model reference adaptive control (MRAC) strategy. Three schemes of the MRAC design have been proposed: the classical MRAC, MRAC with an adaptive disturbance observer, and MRAC with a nonlinear observer. The stability analysis for each scheme has been conducted and developed based on the Lyapunov theorem to prove the uniform ultimate bound of tracking and estimation errors. In addition, the adaptive laws have been developed for the proposed schemes according to the stability analysi

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Yue, Hongyun, Junmin Li, Jiarong Shi, and Wei Yang. "Adaptive Fuzzy Tracking Control for Stochastic Nonlinear Systems with Time-Varying Input Delays Using the Quadratic Functions." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, no. 01 (2018): 109–42. http://dx.doi.org/10.1142/s0218488518500071.

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In this paper, for the stochastic nonlinear systems the adaptive fuzzy tracking controllers are constructed by using the fuzzy logic systems (FLS) and the classical quadratic functions. Compared with the existing results for adaptive fuzzy control, the stochastic nonlinear systems investigated in this paper are much more complex since the systems not only have distributed state time-varying delays in the noise jamming intensity terms but also have the time-varying delays in the input signals. During the controller design procedure, through appropriate assumptions and a state transformation the

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Sheh Zad, Haris, Abasin Ulasyar, Adil Zohaib, and Abraiz Khattak. "Adaptive sliding mode predictive power control of three-phase AC/DC converters." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 236, no. 5 (2022): 897–912. http://dx.doi.org/10.1177/09596518221079469.

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This article presents a new adaptive sliding mode–based model predictive controller for AC/DC three-phase converters achieving better dynamic performance and stability. In the classical model predictive controller available in the literature, the model-based approach, for example, proportional–integral controller is employed for producing the active power reference for the three-phase converters. The traditional proportional–integral–based model predictive controllers consist of steady-state error and slow transient response characteristics. As a result, the DC-link voltage contains uncertaint

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Sands, Timothy. "Comparison and Interpretation Methods for Predictive Control of Mechanics." Algorithms 12, no. 11 (2019): 232. http://dx.doi.org/10.3390/a12110232.

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Objects that possess mass (e.g., automobiles, manufactured items, etc.) translationally accelerate in direct proportion to the force applied scaled by the object’s mass in accordance with Newton’s Law, while the rotational companion is Euler’s moment equations relating angular acceleration of objects that possess mass moments of inertia. Michel Chasles’s theorem allows us to simply invoke Newton and Euler’s equations to fully describe the six degrees of freedom of mechanical motion. Many options are available to control the motion of objects by controlling the applied force and moment. A long,

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Ray, S., G. K. Venayagamoorthy, B. Chaudhuri, and R. Majumder. "Comparison of Adaptive Critic-Based and Classical Wide-Area Controllers for Power Systems." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 38, no. 4 (2008): 1002–7. http://dx.doi.org/10.1109/tsmcb.2008.924141.

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Yang, Mu, Xiaojie Wu, and Maxwell Chiemeka Loveth. "A Deep Reinforcement Learning Design for Virtual Synchronous Generators Accommodating Modular Multilevel Converters." Applied Sciences 13, no. 10 (2023): 5879. http://dx.doi.org/10.3390/app13105879.

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The deep reinforcement learning (DRL) technique has gained attention for its potential in designing “virtual network” controllers. This skill utilizes a novel solution that can avoid the specific parameters and system model required in classical dynamic programming algorithms. However, addressing the issue of system uncertainties and performance deterioration remains a challenge. To overcome this challenge, the authors propose a new control prototype using a twin delayed deep deterministic policy gradient (TD3)-based adaptive controller, which replaces the conventional virtual synchronous gene

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Stanislawski, Radoslaw, Jules-Raymond Tapamo, and Marcin Kaminski. "Virtual Signal Calculation Using Radial Neural Model Applied in a State Controller of a Two-Mass System." Energies 16, no. 15 (2023): 5629. http://dx.doi.org/10.3390/en16155629.

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Neural network approaches have commonly been used to solve complex mathematical equations in the literature. They have inspired the modifications of state controllers and are often implemented for electrical drives with an elastic connection. Given that the addition of a virtual signal can provide adaptive properties to classical controllers and that selected feedback signals can also be replaced with a virtual state variable from a neural network, several combinations can be considered and compared. In this paper, Radial Basis Function neural-network-based control algorithms are proposed in w

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Mehedi, Ibrahim M., Heidir S. M. Shah, Ubaid M. Al-Saggaf, Rachid Mansouri, and Maamar Bettayeb. "Adaptive Fuzzy Sliding Mode Control of a Pressure-Controlled Artificial Ventilator." Journal of Healthcare Engineering 2021 (June 23, 2021): 1–10. http://dx.doi.org/10.1155/2021/1926711.

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This paper presents the application of adaptive fuzzy sliding mode control (AFSMC) for the respiratory system to assist the patients facing difficulty in breathing. The ventilator system consists of a blower-hose-patient system and patient’s lung model with nonlinear lung compliance. The AFSMC is based on two components: singleton control action and a discontinuous term. The singleton control action is based on fuzzy logic with adjustable tuning parameters to approximate the perfect feedback linearization control. The switching control law based on the sliding mode principle aims to minimize t

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Adetifa, A. O., P. P. Okonkwo, B. B. Muhammed, and D. A. Udekwe. "Deep reinforcement learning for aircraft longitudinal control augmentation system." Nigerian Journal of Technology 42, no. 1 (2023): 144–51. http://dx.doi.org/10.4314/njt.v42i1.18.

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Control augmentation systems (CAS) are conventionally built with classical controllers which have the following drawbacks: dependence on domain specific knowledge for tuning and limited self-learning capability. Consequently, these drawbacks lead to sub-optimal aircraft stability and performance when exposed to time varying disturbances. Hence, to curb the stated problems; this paper proposes the development of a deep reinforcement learning (DRL) pitch-rate CAS (qCAS), aimed at guaranteeing adaptive stability, pitch-rate control tracking and disturbance rejection across the longitudinal dynami

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Hassan, Maha Raad, and Shibly Ahmed Al-Samarraie. "Robust Nonlinear Control Design for the HVAC System Based on Adaptive Sliding Mode Control." Journal Européen des Systèmes Automatisés 55, no. 5 (2022): 593–601. http://dx.doi.org/10.18280/jesa.550504.

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Control of Heating, Ventilating, and Air Conditioning (HVAC) aims to provide a comfortable environment for human life in terms of temperature and humidity and improve indoor air quality. The HVAC system is multi-input multi-output, where the control design of this system is challenging due to its strong nonlinearity and the coupled influence of both system controllers on the temperature within the thermal zone. The aim of this study is to design a dual-controller for the HVAC system. The first controller is a non-linear feedback controller which is devoted to control the humidity ratio of the

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Naranjo, José Eugenio, Francisco Serradilla, and Fawzi Nashashibi. "Speed Control Optimization for Autonomous Vehicles with Metaheuristics." Electronics 9, no. 4 (2020): 551. http://dx.doi.org/10.3390/electronics9040551.

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The development of speed controllers under execution in autonomous vehicles within their dynamic driving task (DDT) is a traditional research area from the point of view of control techniques. In this regard, Proportional – Integral – Derivative (PID) controllers are the most widely used in order to meet the requirements of cruise control. However, fine tuning of the parameters associated with this type of controller can be complex, especially if it is intended to optimize them and reduce their characteristic errors. The objective of the work described in this paper is to evaluate the capacity

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Zhang, Lingping, Feng Duan, and Bo Du. "Synchronization Problems of Fuzzy Competitive Neural Networks." Advances in Mathematical Physics 2022 (May 19, 2022): 1–12. http://dx.doi.org/10.1155/2022/5926415.

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This paper is devoted to investigating the fixed-time and finite-time synchronization for fuzzy competitive neural networks with discontinuous activation functions. We introduce Filippov solution for overcoming the nonexistence of classical solutions of discontinuous system. Using the fixed-time synchronization theory, inequality technique, we obtain simple robust fixed-time synchronization conditions. Designing proper feedback controllers is a key step for the implementation of synchronization. Furthermore, based on the fixed-time robust synchronization, we design a switching adaptive control

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Urrea, Claudio, and Yainet Garcia-Garcia. "Design and Performance Analysis of Level Control Strategies in a Nonlinear Spherical Tank." Processes 11, no. 3 (2023): 720. http://dx.doi.org/10.3390/pr11030720.

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This work seeks to contribute to the study of techniques for level control considering a nonlinear plant model. To achieve this goal, different approaches are applied to classical control techniques and their results are analyzed. Fuzzy Logic Control (FLC), Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Model Predictive Control (MPC) and Nonlinear Auto-Regressive Moving Average (NARMA-L2) controllers are designed for the level control of a spherical tank. Subsequently, several tests and scenarios similar to those present in industrial processes are established,

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Ridha, Taghreed Mohammad, and Mina Qays Kadhim. "A Barrier Function-Based Variable Structure Control for Maglev System." Journal Européen des Systèmes Automatisés 55, no. 5 (2022): 633–39. http://dx.doi.org/10.18280/jesa.550508.

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Magnetic levitation (Maglev) systems are widely employed in the industry especially in mechatronics systems for precise positioning and suspension. They are inherently unstable having nonlinear models with uncertain parameters and exposed to external disturbances. Therefore, high-performance robust control designs are recommended for these systems. An Adaptive Variable Structure Controller based on barrier function (AVSCbf) is designed for the first time in this work to control the displacement of the ball position of a disturbed Maglev system. This approach does not require prior knowledge of

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Boz, Utku, and Ipek Basdogan. "A numerical and experimental implementation and integration of Steiglitz–McBride algorithm with the frequency domain IIR filtering technique for active vibration control." Journal of Vibration and Control 24, no. 6 (2016): 1086–100. http://dx.doi.org/10.1177/1077546316657502.

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In adaptive control applications for noise and vibration, finite ımpulse response (FIR) or ınfinite ımpulse response (IIR) filter structures are used for online adaptation of the controller parameters. IIR filters offer the advantage of representing dynamics of the controller with smaller number of filter parameters than with FIR filters. However, the possibility of instability and convergence to suboptimal solutions are the main drawbacks of such controllers. An IIR filtering-based Steiglitz–McBride (SM) algorithm offers nearly-optimal solutions. However, real-time implementation of the SM al

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Ibraheem, Ghusn Abdul Redha, Ahmad Taher Azar, Ibraheem Kasim Ibraheem, and Amjad J. Humaidi. "A Novel Design of a Neural Network-Based Fractional PID Controller for Mobile Robots Using Hybridized Fruit Fly and Particle Swarm Optimization." Complexity 2020 (April 29, 2020): 1–18. http://dx.doi.org/10.1155/2020/3067024.

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The design of a swarm optimization-based fractional control for engineering application is an active research topic in the optimization analysis. This work offers the analysis, design, and simulation of a new neural network- (NN) based nonlinear fractional control structure. With suitable arrangements of the hidden layer neurons using nonlinear and linear activation functions in the hidden and output layers, respectively, and with appropriate connection weights between different hidden layer neurons, a new class of nonlinear neural fractional-order proportional integral derivative (NNFOPID) co

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Zaki Diab, Ahmed A., Abou-Hashema M. El-Sayed, Hossam Hefnawy Abbas, and Montaser Abd El Sattar. "Robust Speed Controller Design Using H_infinity Theory for High-Performance Sensorless Induction Motor Drives." Energies 12, no. 5 (2019): 961. http://dx.doi.org/10.3390/en12050961.

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In this paper, a robust speed control scheme for high dynamic performance sensorless induction motor drives based on the H_infinity (H) theory has been presented and analyzed. The proposed controller is robust against system parameter variations and achieves good dynamic performance. In addition, it rejects disturbances well and can minimize system noise. The H controller design has a standard form that emphasizes the selection of the weighting functions that achieve the robustness and performance goals of motor drives in a wide range of operating conditions. Moreover, for eliminating the spee

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BOUMALHA, NOUREDDINE, DJILLALI KOUCHIH, and MOHAMED SEGHIR BOUCHERIT. "Sensorless Speed and Reactive Power Control of a Double-Feed Induction Generator using Adaptive Observer in Wind Turbine Power Plant." Algerian Journal of Signals and Systems 3, no. 2 (2018): 54–64. http://dx.doi.org/10.51485/ajss.v3i2.59.

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This work presents a new method for the synthesis of a sensorless speed and reactive power control applied to a wind turbine system based to a Doubly Fed Induction Generator (DFIG). The proposed method based on adaptive observers: The rotor speed is adapted using adaptation mechanisms. Stability analysis based on Lyapunov theory is used to guarantee the stability of the observer. To verify the consistency of the proposed approach. We will be interested in the study of vector control based on the synthesis of classical controllers. Simulation results provided with the MATLAB/SIMULINK environmen

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Ceballos Benavides, Gustavo E., Manuel A. Duarte-Mermoud, Marcos E. Orchard, and Juan Carlos Travieso-Torres. "Pitch Angle Control of an Airplane Using Fractional Order Direct Model Reference Adaptive Controllers." Fractal and Fractional 7, no. 4 (2023): 342. http://dx.doi.org/10.3390/fractalfract7040342.

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This paper deals with the longitudinal movement control of an airplane (pitch angle) using fractional order adaptive controllers (FOACs). It shows the improvements achieved in the plane’s behavior, in terms of the minimization of a given performance index. At the same time, less control effort is needed to accomplish the control objectives compared with the classic integer order adaptive controllers (IOACs). In this study, fractional order direct model reference adaptive control (FO-DMRAC) is implemented at the simulation level, and exhibits a better performance compared with the classic integ

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Momeni, Z., and A. Bagchi. "Intelligent Control Methodology for Smart Highway Bridge Structures Using Optimal Replicator Dynamic Controller." Civil Engineering Journal 9, no. 1 (2023): 1–16. http://dx.doi.org/10.28991/cej-2023-09-01-01.

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Control algorithms are an essential part of effective semi-active vibration control systems used for the protection of large structures under dynamic loading. Adaptive control algorithms, which are data-driven methods, have recently been developed to replace model-based control algorithms, thus improving efficiency. The dynamic parameters of semi-actively controlled infrastructures will change after significant vibration loading. As a result, these structures require real-time, effective control actions in response to changing conditions, which classical controllers are unable to provide. To i

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Sengupta, Ipsita, Sagar Gupta, Dipankar Deb, and Stepan Ozana. "Dynamic Stability of an Electric Monowheel System Using LQG-Based Adaptive Control." Applied Sciences 11, no. 20 (2021): 9766. http://dx.doi.org/10.3390/app11209766.

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This paper presents the simulation and calculation-based aspect of constructing a dynamically stable, self-balancing electric monowheel from first principles. It further goes on to formulate a reference model-based adaptive control structure in order to maintain balance as well as the desired output. First, a mathematical model of the nonlinear system analyzes the vehicle dynamics, followed by an appropriate linearization technique. Suitable parameters for real-time vehicle design are calculated based on specific constraints followed by a proper motor selection. Various control methods are tes

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Znidi, Aicha, Khadija Dehri, and Ahmed Said Nouri. "Discrete indirect adaptive sliding mode control for uncertain Hammerstein nonlinear systems." Transactions of the Institute of Measurement and Control 44, no. 10 (2022): 1907–21. http://dx.doi.org/10.1177/01423312211067801.

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The robustness issue of uncertain nonlinear systems’ control has attracted the attention of numerous researchers. In this paper, we propose three techniques to deal with the uncertain Hammerstein nonlinear model. First, a discrete sliding mode control (SMC) is developed, which is based on converting the original nonlinear system into a linearized one in the vicinity of the operating region using Taylor series expansion. However, the presence of relatively high nonlinearities and parameter variations leads to the deterioration of the desired performances. In order to overcome these problems and

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Lai, Pengyu, Yi Liu, Wei Zhang, and Hui Xu. "Intelligent controller for unmanned surface vehicles by deep reinforcement learning." Physics of Fluids 35, no. 3 (2023): 037111. http://dx.doi.org/10.1063/5.0139568.

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With the development of the applications of unmanned surface vehicles (USVs), USV automation technologies are attracting increasing attention. In the industry, through the subtask division, it is generally believed that course-keeping is a critical basic sub-system in a series of complex automation systems and affects USV automation performance to a great extent. By course-keeping, we mean USV adjusts its angle to the desired angle and keeps it. In recent decades, course-keeping has been mainly achieved through classical first principles technologies, such as proportion–integral–differential (

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