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1 – 10 of 786Abdeldjabar Benrabah and Dianguo Xu
The purpose of this study is to improve the control performance of grid-connected photovoltaic (PV) inverters with inductive-capacitive-inductive (LCL) filters by proposing a new…
Abstract
Purpose
The purpose of this study is to improve the control performance of grid-connected photovoltaic (PV) inverters with inductive-capacitive-inductive (LCL) filters by proposing a new robust current control based on uncertainty and disturbance estimator (UDE).
Design/methodology/approach
The control strategy combines the capacitor current feedback with a UDE-based control to solve robust stability issues in the presence of parametric uncertainties and disturbances.
Findings
This paper provides guidelines for tuning the controller parameters where it is shown to be easy to implement by simply selecting the appropriate feedback coefficient, the reference model and an approximate lumped disturbance bandwidth. Simulation and experimental results demonstrate the effectiveness of the proposed controller in terms of resonance damping, tracking performance and robust stability under grid uncertainties and disturbances.
Practical implications
This paper offers a new approach for designing implementable robust controllers for LCL-filtered grid-connected PV inverters.
Originality/value
A new UDE-based current control is proposed to improve the stability performance of grid-connected PV inverters. The advantages of UDE-based control are its simple structure, easy tuning and robustness under parameter uncertainties and disturbances. Simulation and experimental results support the theoretical findings.
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Abdeldjabar Benrabah, Farid Khoucha, Ali Raza and Mohamed Benbouzid
The purpose of this study is to improve the control performance of wind energy conversion systems (WECSs) by proposing a new sensorless, robust control strategy based on a Smith…
Abstract
Purpose
The purpose of this study is to improve the control performance of wind energy conversion systems (WECSs) by proposing a new sensorless, robust control strategy based on a Smith predictor active disturbance rejection control (SP-ADRC) associated with a speed/position estimator.
Design/methodology/approach
The estimator consists of a sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate the permanent magnet synchronous generator (PMSG) rotor position and speed. At the same time, the SP-ADRC is applied to the speed control loop of the variable-speed WECS control system to adapt strongly to dynamic characteristics under parameter uncertainties and disturbances.
Findings
Numerical simulations are conducted to evaluate the speed tracking performances under various wind speed profiles. The results show that the proposed sensorless speed control improves the accuracy of rotor speed and position estimation and provides better power tracking performance than a regular ADRC controller under fast wind speed variations.
Practical implications
This paper offers a new approach for designing sensorless, robust control for PMSG-based WECSs.
Originality/value
A new sensorless, robust control is proposed to improve the stability and tracking performance of PMSG-based WECSs. The SP-ADRC control attenuates the effects of parameter uncertainties and disturbances and eliminates the time-delay impact. The sensorless control design based on SMO and PLL improves the accuracy of rotor speed estimation and reduces the chattering problem of traditional SMO. The obtained results support the theoretical findings.
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Dinesh D. Dhadekar, Ajay Misra and S.E. Talole
The purpose of the paper is to design a nonlinear dynamic inversion (NDI) based robust fault-tolerant control (FTC) for aircraft longitudinal dynamics subject to system…
Abstract
Purpose
The purpose of the paper is to design a nonlinear dynamic inversion (NDI) based robust fault-tolerant control (FTC) for aircraft longitudinal dynamics subject to system nonlinearities, aerodynamic parametric variations, external wind disturbances and fault/failure in actuator.
Design/methodology/approach
An uncertainty and disturbance estimator (UDE) technique is used to provide estimate of total disturbance enabling its rejection and thereby achieving robustness to the proposed NDI controller. As needed in the NDI design, the successive derivatives of the output are obtained through an UDE robustified observer making the design implementable. Further, a control allocation scheme consigns control command from primary actuator to the secondary one in the event of fault/failure in the primary actuator.
Findings
The robustness is achieved against the perturbations mentioned above in the presence of actuator fault/failure.
Practical implications
Lyapunov analysis proves practical stability of the controller–observer structure. The efficacy and superiority of the proposed design has been demonstrated through Monte-Carlo simulation.
Originality/value
Unlike in many FTC designs, robustness is provided against system nonlinearities, aerodynamic parametric variations, external wind disturbances and sinusoidal input disturbance using a single control law which caters for fault-free, as well as faulty actuator scenario.
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Mati Ullah, Chunhui Zhao and Hamid Maqsood
The purpose of this paper is to design a hybrid robust tracking controller based on an improved radial basis function artificial neural network (IRBFANN) and a novel…
Abstract
Purpose
The purpose of this paper is to design a hybrid robust tracking controller based on an improved radial basis function artificial neural network (IRBFANN) and a novel extended-state observer for a quadrotor system with various model and parametric uncertainties and external disturbances to enhance the resiliency of the control system.
Design/methodology/approach
An IRBFANN is introduced as an adaptive compensator tool for model and parametric uncertainties in the control algorithm of non-singular rapid terminal sliding-mode control (NRTSMC). An exact-time extended state observer (ETESO) augmented with NRTSMC is designed to estimate the unknown exogenous disturbances and ensure fast states convergence while overcoming the singularity issue. The novelty of this work lies in the online updating of weight parameters of the RBFANN algorithm by using a new idea of incorporating an exponential sliding-mode effect, which makes a remarkable effort to make the control protocol adaptive to uncertain model parameters. A comparison of the proposed scheme with other conventional schemes shows its much better performance in the presence of parametric uncertainties and exogenous disturbances.
Findings
The investigated control strategy presents a robust adaptive law based on IRBFANN with a fast convergence rate and improved estimation accuracy via a novel ETESO.
Practical implications
To enhance the safety level and ensure stable flight operations by the quadrotor in the presence of high-order complex disturbances and uncertain environments, it is imperative to devise a robust control law.
Originality/value
A new idea of incorporating an exponential sliding-mode effect instead of conventional approaches in the algorithm of the RBFANN is used, which makes the control law resistant to model and parametric uncertainties. The ETESO provides rapid and accurate disturbance estimation results and updates the control law to overcome the performance degradation caused by the disturbances. Simulation results depict the effectiveness of the proposed control strategy.
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Mohammad Mehdi Fateh and Siamak Azargoshasb
The purpose of this paper is to design a discrete indirect adaptive fuzzy controller for a robotic manipulator. This paper addresses how to overcome the approximation error of the…
Abstract
Purpose
The purpose of this paper is to design a discrete indirect adaptive fuzzy controller for a robotic manipulator. This paper addresses how to overcome the approximation error of the fuzzy system and uncertainties for asymptotic tracking control of robotic manipulators. The uncertainties include parametric uncertainty, un-modeled dynamics, discretization error and external disturbances.
Design/methodology/approach
The proposed controller is model-free and voltage-based in the form of discrete-time Mamdani fuzzy controller. The parameters of fuzzy controller are adaptively tuned for asymptotic tracking of a desired trajectory. A robust control term is used to compensate the approximation error of the fuzzy system. An adaptive mechanism is derived based on the stability analysis.
Findings
The proposed model-free discrete control is robust against all uncertainties associated with the robot manipulator and actuators. The approximation error of the fuzzy system is well compensated to achieve asymptotic tracking of the desired trajectories. Stability analysis and simulation results show its efficiency in the tracking control.
Originality/value
A novel discrete indirect adaptive fuzzy controller is designed for electrically driven robot manipulators using the voltage control strategy. The novelty of this paper is compensating the approximation error of the fuzzy system and discretizing error for asymptotic tracking of the desired trajectory.
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mohammad mehdi fateh and Mohaddeseh Amerian
A hydraulic elevator including the hydraulic actuator and cabin is highly nonlinear with many parameters and variables. Its state-space model is in non-companion form and…
Abstract
Purpose
A hydraulic elevator including the hydraulic actuator and cabin is highly nonlinear with many parameters and variables. Its state-space model is in non-companion form and uncertain due to the parametric errors, flexibility of the ropes, friction and external load disturbances. A model-based control cannot perform well while a precise model is not available and all state variables cannot be measured. To overcome the problems, this paper aims to develop a direct adaptive fuzzy control (DAFC) for the hydraulic elevator.
Design/methodology/approach
The controller is an adaptive PD-like Mamdani type fuzzy controller using position error and velocity error as inputs. The design is based on the stability analysis.
Findings
The proposed control can overcome uncertainties, guarantee stability, provide a good tracking performance and operate as active vibration suppression by tracking a smooth trajectory. The controller is not involved in the nonlinearity, uncertainty and vibration of the system due to being free from model. Its performance is superior to a PD-like fuzzy controller due to being adaptive as illustrated by simulations.
Originality/value
The proposed DAFC is applied for the first time on the hydraulic elevator. Compared to classic adaptive fuzzy, it does not require all system states. In addition, it is not limited to the systems, which have the state-space model in companion form and constant input gain, thus is much less computational and easier to implement.
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Tim Chen, Nai Jau Dkuo and C.Y.J. Chen
This paper aims to propose a composite form of the robust disturbance fuzzy control scheme. The proposed method uses the benefits of fuzzy system modeling and Lyapunov direct…
Abstract
Purpose
This paper aims to propose a composite form of the robust disturbance fuzzy control scheme. The proposed method uses the benefits of fuzzy system modeling and Lyapunov direct methods.
Design/methodology/approach
The effciency of the control technique was demonstrated with assistance of numerical simulation in control problems of unmanned aerial vehicle (UAV) simulation.
Findings
To evaluate the control performance, the comparison of the proposed controller was made with conventional control techniques. The Lyapunov stability theorem has been used to testify for asymptotic stability and convergence of the closed loop system.
Practical implications
Implementation of the control law in the real world environment can be easier due to significant reduction in the fuzzy rules, tuning parameters and computation stages.
Originality/value
Simulation results confirm that the proposed control scheme performs remarkably well in terms of the robustness and disturbance attenuation.
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Jafar Keighobadi, Mohammad‐Javad Yazdanpanah and Mansour Kabganian
The purpose of this paper is to consider the process of design and implementation of an enhanced fuzzy H∞ (EFH∞) estimation algorithm to determine the attitude and heading angles…
Abstract
Purpose
The purpose of this paper is to consider the process of design and implementation of an enhanced fuzzy H∞ (EFH∞) estimation algorithm to determine the attitude and heading angles of ground vehicles, which are frequently affected by considerable exogenous disturbances. To detect the changes of disturbances, a fuzzy system is designed based on expert knowledge and experiences of a navigation engineer. In the EFH∞ estimator, the intensity bounds of disturbances affecting the measurements are updated using a heuristic combination of three change‐detection indices. Performance of the proposed estimator is evaluated by Monte‐Carlo simulations and field tests of three kinds of vehicles using a manufactured attitude‐heading reference system (AHRS). In both simulations and real tests, the proposed estimator results in a superior performance compared to those of the recently developed and standard H∞ estimators.
Design/methodology/approach
Design, implementation and real tests of the EFH∞ estimator are considered for an AHRS specialized for vehicular applications. In the AHRS, three‐axis accelerometers (TAA) and three‐axis magnetometers (TAM) may be affected by large disturbances due to non‐gravitational accelerations and local magnetic fields. Therefore, the design parameters of EFH∞ estimator including the theoretic bound of disturbance intensity and the attenuation level are adaptively tuned using a fuzzy combination of three change‐detection indices. Once a sensor is affected by an exogenous disturbance, the fuzzy system will increase the scale factor of the corresponding measurement disturbance to place more confidence on the data of the AHRS dynamics including measurements of gyros with respect to the data coming from the TAA and TAM.
Findings
An intelligent fault detector is proposed for considering changes of disturbances to adjust the upper bounds of the estimator's disturbances and the length of data to update the fuzzy system inputs. The EFH∞ estimator is suitable to attenuate the effects of disturbances changes on accurate estimation of the attitude and heading angles, intelligently.
Originality/value
The paper provides a fuzzy state estimator for adaptively adjusting the theoretic disturbance matrices according to the actual intensity of the disturbances affecting the AHRS dynamics and the measurement sensors.
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Alon Kuperman, Yoram Horen, Saad Tapuchi, Inna Katz and Alexander Abramovitz
The purpose of this paper is to present a method to compensate slow varying disturbances and plant parameter drifts using a simple yet robust algorithm called input‐output…
Abstract
Purpose
The purpose of this paper is to present a method to compensate slow varying disturbances and plant parameter drifts using a simple yet robust algorithm called input‐output nominalization.
Design/methodology/approach
In case of known uncertainties, an analytical expression of pre‐computed feed‐forward compensation command is derived. In presence of unknown disturbances and parameter drifts, the control algorithm uses a proportional‐integrative estimator‐based nominalizer. It creates a nominalizing signal, reflecting the deviation of the system from its nominal form using plant input and output. The signal is subtracted from the nominal controller output to cancel the uncertainty and disturbances effects.
Findings
As a result, the uncertain plant and the nominalizer quickly converge to the nominal plant. Therefore, a simple controller tuned according to the nominal plant can be used despite the disturbances and parameter drifts and a nominal response is always obtained. Simulation and experimental results are given to describe the control algorithm performance and inherent limitations.
Research limitations/implications
The proposed method is suitable for linear systems with low frequency uncertainties and disturbances only.
Practical implications
The technique allows compensating errors in plant parameter identifications as well as parameter drifts during plant operations. Constant and slow varying disturbances are also rejected, allowing obtaining a prescribed nominal response.
Originality/value
The proposed approach is different from the common robust control methods to the uncertain linear systems control. Instead of designing a robust controller, efforts are concentrated on the plant input‐output nominalization in a fashion similar to input‐output linearization. The method allows compensating slow varying disturbances and plant parameter drifts using a simple algorithm leading to a simple controller tuned according to the nominal plant parameters.
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Mohammad Mehdi Fateh, Siamak Azargoshasb and Saeed Khorashadizadeh
– Discrete control of robot manipulators with uncertain model is the purpose of this paper.
Abstract
Purpose
Discrete control of robot manipulators with uncertain model is the purpose of this paper.
Design/methodology/approach
The proposed control design is model-free by employing an adaptive fuzzy estimator in the controller for the estimation of uncertainty as unknown function. An adaptive mechanism is proposed in order to overcome uncertainties. Parameters of the fuzzy estimator are adapted to minimize the estimation error using a gradient descent algorithm.
Findings
The proposed model-free discrete control is robust against all uncertainties associated with the model of robotic system including the robot manipulator and actuators, and external disturbances. Stability analysis verifies the proposed control approach. Simulation results show its efficiency in the tracking control.
Originality/value
A novel model-free discrete control approach for electrically driven robot manipulators is proposed. An adaptive fuzzy estimator is used in the controller to overcome uncertainties. The parameters of the estimator are regulated by a gradient descent algorithm. The most gradient descent algorithms have used a known cost function based on the tracking error for adaptation whereas the proposed gradient descent algorithm uses a cost function based on the uncertainty estimation error. Then, the uncertainty estimation error is calculated from the joint position error and its derivative using the closed-loop system.
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