Search

To address the impact of load variations, external environmental changes, and the tuning of the parameters on Permanent Magnet Synchronous Motors (PMSMs) used in ships, this study proposes an Active Disturbance Rejection Control (ADRC) strategy for PMSMs, optimized by the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm. First, based on the PMSM model, the study addresses the limited disturbance rejection capability of the traditional fal function in the Extended State Observer (ESO) of conventional ADRC. To improve the accuracy of the state observer, the faln function is introduced as a replacement for the traditional fal function. Second, due to the numerous parameters in ADRC, which are difficult to tune, the QPSO algorithm—known for its strong global search capabilities and fast convergence speed—is utilized for parameter optimization. Additionally, the position update formula within the optimization algorithm is revised and optimized. Finally, simulation experiments are conducted using the Matlab/Simulink platform, where practical conditions, such as load fluctuations and random noise, are incorporated. The simulation results demonstrate that, compared to PSO-ADRC control, IPSO-ADRC control, and ICFO-ADRC control, the proposed method offers a superior dynamic response. Specifically, the speed control accuracy is improved by 46.7%, torque ripple is reduced by 50.8%, and harmonic distortion decreases by 23.1%. These results highlight the significant advantages of this method in enhancing system robustness, dynamic response speed, and steady-state accuracy, making it particularly suitable for PMSM control systems in complex dynamic environments, such as those encountered on ships. [ABSTRACT FROM AUTHOR]

Disturbances and uncertainties, ubiquitous in real‐world systems, complicate model‐based control design. A key challenge is developing a precise control strategy that takes all disturbances into account. The automatic dry‐type clutch is a nonlinear, uncertain, and continuous system, where influencing factors are regarded as total disturbances. An active disturbance rejection control (ADRC) framework with an adaptive extended state observer (AESO) is proposed. The AESO's key strength is its adaptability, adjusting gains over time to minimize state estimation errors and noise impacts. This optimizes disturbance estimation, enhancing closed‐loop system performance. Furthermore, we prove the stability of the AESO through the Lyapunov method and, based on this, set the controller parameters as a Hurwitz matrix to ensure the stability of the closed‐loop system. Experimental data from clutch control demonstrates the efficacy of this controller. It ensures clutch position accuracy with a mean value of 13.5255 mm and a root mean square error of 28.7368 mm. Notably, the AESO's observation errors are minimal, averaging at 0.4365 mm with a root mean square error of 0.7068 mm, even under conditions of uncertain dynamics and measurement noise. This performance surpasses traditional ADRC methods relying on linear extended state observers (ESO) and PI control, thereby advancing the practical applicability of ADRC. Finally, through simulations comparing with fuzzy ESO and nonlinear ESO, the results show that the proposed AESO can achieve the same effect as them. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 causes a serious threat to human health and life around the world and puts enormous pressure on the healthcare system. The lockdown policy has effectively reduced the number of cases and suppressed the spread of the COVID-19 epidemic, but it also requires high social and economic costs. In this paper, we aim to use feedback control to help decision-makers establish lockdown policies, which can effectively constrain the spread of the COVID-19 pandemic with minimal financial loss. The time-dependent susceptible-infected-removed (SIR) model is used for the dynamics of the COVID-19 pandemic. The feedback control is based on a modified nonlinear active disturbance rejection controller (ADRC) that includes modified nonlinear extended state and nonlinear state error feedback with parameters tuned by particle swarm optimization, and the performances are compared with a well-known proportional-–integral–-derivative (PID) controller. The final simulation results show that the modified nonlinear ADRC has better performances and is more robust against uncertainties in the parameters of the epidemiological model. [ABSTRACT FROM AUTHOR]

An active disturbance rejection control (ADRC) has been developed for stabilizing electric vehicle (EV) systems without the need for model identification. The proximal policy optimization (PPO) algorithm, along with actor and critic neural networks, has been used to fine-tune the adjustable parameters of the ADRC controller to achieve optimal performance in a specific case study. The architecture of PPO implements separate neural networks and ameliorates the PPO adaptability to handle continuous action spaces. By maximizing a reward function based on system output, the PPO agent optimally tunes the gains to reduce undesired speed fluctuations of EVs and improve system stability. Performance evaluation under the new European driving cycle and federal test procedure has been conducted to examine the feasibility of the suggested controller. The disturbance rejection capability of the ADRC controller designed by the PPO algorithm has been tested and compared with prevalent control methodologies. Moreover, real-time examinations of the dynamic behavior of EV systems have been made to identify the capability of the suggested controller in real-world hardware. The results show that the suggested controller outperforms other designed controllers in terms of transient behavior and numerical performance metrics. [ABSTRACT FROM AUTHOR]

Reasonable and effective control of a cathode air supply system is conducive to improving the dynamic response, operating efficiency, and reliability of fuel cell systems. This paper proposes a novel data-driven adaptive oxygen excess ratio (OER) control strategy based on online parameter identification for fuel cell systems. The proposed control scheme employs a second-order active disturbance rejection controller (ADRC) derived from the proportional-integral-derivative tuning rule to effectively deal with model uncertainties and external disturbances. Online parameter identification continuously translates the cathode air supply system into the second-order model, enabling the real-time adaptation of controller parameters to varying operating conditions. Simulation results demonstrate that the OER control strategy proposed significantly improves voltage stability and system efficiency under dynamic conditions compared to traditional methods. The innovation of this paper is that, based on consideration of the nonlinear slow time-varying characteristics of a PEMFC and the frequent disturbance of load current, adaptive control under system dynamic conditions can be considered. Combining the parameter identification scheme, an adaptive online self-tuning scheme is designed for the identified system model, which avoids the tediousness of a complex modeling process and has promotion value in practical applications. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The grid connection guidelines require wind turbines to have capability to quickly support reactive power in the events of grid faults. However, traditional proportional-integral controllers have the problems of slow transient response and poor adaptability dealing with changes in grid impedance and serious model disturbances. In order to solve this problem, this paper proposes an improved reactive power support control strategy which combines linear active disturbance rejection control(ADRC) with least error squares(LES) filters. The LES filter is used to quickly and accurately detect the amplitude of the fault grid voltage with background harmonics, which can effectively reduce the fault detection delay. The ADRC controller is used to effectively improve the transient reactive power response speed and the control adaptability and robustness of the wind turbines under grid impedance disturbance. The simulation model of direct drive wind turbine based on PSCAD/EMTDC is built considering two scenarios, weak power grid and power grid with background harmonics. The effectiveness of the proposed control strategy is verified by simulation.

To address the issue of multi-body folding wings being subjected to aerodynamic load changes, gravity reversal, and external disturbances during coordinated tilting, an improved active disturbance rejection control (ADRC) strategy based on the combination of hyperbolic tangent function and phase compensation is proposed. Using the Lagrange equation, the aerodynamic load on the unit wing is applied to the center of mass, and the offset of the gravity term with the attitude angle of the body is provided, thereby establishing the dynamic model of the multi-body folding wing. An improved ADRC controller is designed to track the desired angular trajectory of the folding wing, and appropriate controller parameters are selected to suppress joint vibration. The simulation results show that the improved ADRC method can effectively achieve trajectory tracking and joint vibration suppression under variable load conditions, and it demonstrates smaller tracking errors and better dynamic performance and robustness when subjected to external disturbances.

Abstract Aiming at the oscillation caused by the hydraulic cylinder of independent metering system (IMS) running between multiple working quadrants, a novel multiple quadrants switching displacement tracking control strategy is proposed in this paper. In this control strategy, both the cylinder chamber pressure under resistance and overrunning conditions are controlled by the inlet valve, and the outlet valve is utilized to control the displacement of cylinder. This method allows the hydraulic cylinder to always run in energy-efficient. When the working quadrant changes, the valve’s working modes are unchanged, which avoids oscillation caused by changes of valves working modes in principle. And a reduced-order active disturbance rejective displacement controller and an active disturbance rejective pressure controller are designed to get high-precision tracking of the displacement and pressure. Numerous experimental results show that the proposed method is reasonable and effective, hydraulic cylinder operates smoothly between multiple quadrants, the pressure and displacement controllers have good anti-interference ability and robustness, and the energy consumption can be reduced by more than 23% compared to the traditional constant pressure valve control system.

For the attitude control problem of quadrotor affected by external disturbance and modeling uncertainty, an active disturbance rejection attitude control method which consisted of a fixed-time reduced-order extended state observer (RESO) and a fixed-time backstepping state feedback controller was proposed. Based on the quadrotor dynamics model and active disturbance rejection control(ADRC) theory, firstly, a RESO with fixed-time convergence property was designed and the convergence of the observer was proved theoretically. Secondly, a based on the backstepping control theory, a fixed-time backstepping controller was designed combined with the fixed-time control theory, and it was theoretically proved that the tracking error of closed loop system can converge to the origin at fixed time. Finally, the performance of the proposed control algorithm was investigated from the indexes of rise time, steady-state error, maximum error and mean square error through simulation cases. The simulation results demonstrate that the proposed improved method has better control quality compared to the traditional ADRC and backstepping sliding mode control. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we uncover a new connection between standard proportional‐integral (PI), proportional‐integral‐derivative (PID) controllers and active disturbance rejection control (ADRC), from which we establish formal conditions of equivalence between the two control schemes. Using the equivalence, we devise a step‐by‐step procedure of transitioning from PI/PID to error‐based ADRC. We also show how to go from one degree‐of‐freedom (1DOF) to two degree‐of‐freedom (2DOF) ADRC while retaining a standard 2DOF PI/PID structure. Both procedures facilitate expressing error‐based ADRC schemes as standard industrial 1DOF and 2DOF controllers. This allows the designed controller to have the desired characteristic of ADRC (i.e., strong robustness against internal and external uncertainties) while still being expressed in a form that is familiar to industrial practitioners, where PI/PID structures are still the workhorse of modern control systems. The paper's results ensure backward compatibility of future ADRC‐based solutions and foster the adoption of active disturbance rejection‐based methods in industrial practice as a viable alternative to standard controllers. To further support the findings, a set of tests is conducted in time and frequency domain. [ABSTRACT FROM AUTHOR]

Automatic splicing of interrupted yarns in ring spinning has always been a problem in the industry. Factors such as low yarn strengths and environmental influence on yarn tensions make it difficult to control the yarn tension during the robotic splicing process. The purpose of this research is to design active disturbance rejection control (ADRC) for a third-order nonlinear tension system subject to external disturbances. Firstly, a third-order extended state observer (ESO) is designed to achieve the suppression and the compensation of the internal modeling error and the external disturbances of the system. Secondly, the adaptive gain error feedback control and the filtering process are designed to reduce the influence of sensor noise on the disturbance observation. Finally, the tension control during the splicing process is simulated and experimented, and the experiments show that the method has good robustness in the tension tracking task under a dynamic environment, which verifies the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Aiming at the oscillation caused by the hydraulic cylinder of independent metering system (IMS) running between multiple working quadrants, a novel multiple quadrants switching displacement tracking control strategy is proposed in this paper. In this control strategy, both the cylinder chamber pressure under resistance and overrunning conditions are controlled by the inlet valve, and the outlet valve is utilized to control the displacement of cylinder. This method allows the hydraulic cylinder to always run in energy-efficient. When the working quadrant changes, the valve’s working modes are unchanged, which avoids oscillation caused by changes of valves working modes in principle. And a reduced-order active disturbance rejective displacement controller and an active disturbance rejective pressure controller are designed to get high-precision tracking of the displacement and pressure. Numerous experimental results show that the proposed method is reasonable and effective, hydraulic cylinder operates smoothly between multiple quadrants, the pressure and displacement controllers have good anti-interference ability and robustness, and the energy consumption can be reduced by more than 23% compared to the traditional constant pressure valve control system. [ABSTRACT FROM AUTHOR]

Active disturbance rejection controller (ADRC) has been widely promoted in permanent magnet synchronous motor (PMSM) drives for its simple design and remarkable anti‐disturbance characteristics. To further improve the control performance, a variety of advanced ADRC schemes have been proposed in recent years. However, the majority of them focused on constructing more complicated extended state observers (ESOs) while ignoring the utilization of state feedback. Motivated by the above issue, this article proposes an enhanced virtual friction ADR speed controller (VFADRC). It is distinguished by the simpler structure compared with other ADRC schemes. Besides, the introduced zero in disturbance rejection function of VFADRC contributes to the preferable anti‐disturbance response. Moreover, the enhanced configuration of VFADRC proposed in the article further improves the speed dynamics and robustness to inertia variations. Both the theoretical analysis and experimental results validate the excellent performance of the proposed ADR controller. [ABSTRACT FROM AUTHOR]

Active disturbance rejection control (ADRC) is considerably applied due to its advantage of focusing on merely dominant parameters. Research on flexible systems frequently confronting perplexing disturbances can utilize this method to simplify irrelevant items as a single variable. In this paper, we focused on vibration control problems in flexible systems with the application of ADRC and constructed a second‐order system model under the guideline of fundamental principles of ADRC and an innovative algorithm for tuning feedforward compensation ADRC. During the simulation, we discussed three cases in which each solely one parameter varies while others are kept invariant. Time, open‐loop frequency, and close‐loop frequency responses were respectively analyzed in all cases as to determine the stability of the system. According to the simulation results, we arrived at the conclusion: we should choose the specification of a flexible system within an intermediate range and evade from critical system parameters to procure stability and efficiency. [ABSTRACT FROM AUTHOR]

In the last decade, quadrotors have gained popularity among industry and academia due to their capabilities and the various applications in which they can be found. In addition to the above, because this is an underactuated system, researchers have found it a great challenge to control. Despite this, there is a wide variety of methodologies in the literature to control this type of system. Based on the above, this work proposed an alternative to trajectory tracking control for quadrotor unmanned aerial vehicles (UAV). The problem was divided into two main control loops: an outer control loop for the position coordinates, tackled through linear active disturbance rejection controllers (ADRC), and an inner control loop related to the orientation variables, addressed via robust proportional-integral-differential (PID) controllers. Furthermore, a generalized proportional integral observer (GPIO) was implemented to estimate the velocity and internal and external disturbances; therefore, the control strategy only depended on the attitude (position and orientation) quadrotor measurements. Then, the control performance was tested through numerical simulations and experimental tests, including wind disturbance inputs. [ABSTRACT FROM AUTHOR]

Copyright of Information & Control is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Lately, active disturbance rejection control (ADRC), a model-independent controller, has become popular for combating various forms of uncertain disturbances incurred in industrial applications. ADRC was validated for external disturbances, internal disturbances, and nonlinearities incurred under realistic scenarios. Time delay challenges all controllers, especially when it coexists with nonlinearities. This paper investigates the impacts of time delay and backlash-like hysteresis nonlinearity in ADRC-controlled systems. These impacts are analyzed, as in the case study, in two ADRC-based methods, namely the ADRC with delayed input method and the predictive extended state observer (PESO)-based ADRC (PESO-ADRC) method. To improve the system response and to attain a decent attenuation of uncertainties, the time-delay estimation (TDE) mechanism is introduced to the concerned ADRC-based methods. Experimental studies are conducted to verify the effectiveness and stability of the proposed TDE-ADRC methods. The results demonstrate the robustness and decent recovery of the transient response after the adverse impact of the backlash-like hysteresis on both concerned ADRC-controlled systems. [ABSTRACT FROM AUTHOR]

To address the internal and external disturbances in Permanent Magnet Synchronous Motor (PMSM) such as modeling errors and sudden load variation, a load estimation-based composite Active Disturbance Rejection Control (ADRC) approach is proposed for PMSM speed regulation. ADRC is adopted to replace the PI controller in the speed loop to improve the performance of control system and solve the contradiction between system rapidity and overshooting. A load torque observer is designed to correct the slow response of ESO to sudden load variation by directly estimating and compensating the load torque in real time via speed and current signals. Additionally, a semi-physical experimental platform of composite ADRC for speed regulation is constructed in Matlab/Simulink environment, and the proposed composite ADRC is compared with traditional PI control and linear ADRC. The results illustrate that the proposed approach outperforms conventional controller by reducing the speed variation by more than 30% under abrupt load variation, and has superior disturbance rejection ability and speed regulation performance. [ABSTRACT FROM AUTHOR]

Permanent magnet synchronous motor (PMSM) speed control systems with conventional linear active disturbance rejection control (CLADRC) strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances. In order to address these issues, this paper proposes an improved two-degree-of-freedom LADRC (TDOF-LADRC) strategy, which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning. PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately. Moreover, to evaluate the control performance of the TDOF-LADRC strategy, its stability is proven, and the influence of each controller parameter on the system control performance is analyzed. Based on it, a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances. Finally, experiments are performed on a 750 W PMSM experimental platform, and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

To address the impact of load variations, external environmental changes, and the tuning of the parameters on Permanent Magnet Synchronous Motors (PMSMs) used in ships, this study proposes an Active Disturbance Rejection Control (ADRC) strategy for PMSMs, optimized by the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm. First, based on the PMSM model, the study addresses the limited disturbance rejection capability of the traditional fal function in the Extended State Observer (ESO) of conventional ADRC. To improve the accuracy of the state observer, the faln function is introduced as a replacement for the traditional fal function. Second, due to the numerous parameters in ADRC, which are difficult to tune, the QPSO algorithm—known for its strong global search capabilities and fast convergence speed—is utilized for parameter optimization. Additionally, the position update formula within the optimization algorithm is revised and optimized. Finally, simulation experiments are conducted using the Matlab/Simulink platform, where practical conditions, such as load fluctuations and random noise, are incorporated. The simulation results demonstrate that, compared to PSO-ADRC control, IPSO-ADRC control, and ICFO-ADRC control, the proposed method offers a superior dynamic response. Specifically, the speed control accuracy is improved by 46.7%, torque ripple is reduced by 50.8%, and harmonic distortion decreases by 23.1%. These results highlight the significant advantages of this method in enhancing system robustness, dynamic response speed, and steady-state accuracy, making it particularly suitable for PMSM control systems in complex dynamic environments, such as those encountered on ships.

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Drive is the property of Electric Drive Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ObjectiveIn order to improve the safe and stable operation level of compressor equipment, this paper puts forward a rapid diagnosis method of surge states based on hybrid deep learning parameter identification, and proposes an active disturbance rejection control (ADRC) strategy to realize compressor anti-surge. MethodFirst, a long-short-term memory neural network (LSTM) is used to process the time series relationship of the input and output data for compressor parameter identification; the interval probability estimation ability of Gaussian process regression (GPR) is integrated; a combination of LSTM and GPR (LSTM-GPR) is proposed; and a hybrid deep learning parameter identification algorithm is used to realize the rapid diagnosis of the compressor surge state. Then, based on the ADRC method, the parameters of the compressor's throttle valve are controlled, and the accurate control of the surge state of the compressor is realized through the compensation of the throttle valve parameters by the control amount. ResultsThe results show that the hybrid deep learning parameter identification algorithm can accurately identify the critical Greitzer parameters of the compressor and quickly and accurately judge whether it is in a surge state, and the ADRC-based control strategy can effectively allow the compressor to exit the surge state, which is faster and more effective than traditional PID control and nonlinear feedback control without losing the working range of the compressor. ConclusionThe proposed parameter identification and ADRC method can be applied to the surge diagnosis and active control of compressors to improve their safety and stability.

This article proposes the theoretical development and experimental application of the active disturbance rejection control (ADRC) to synchronous reluctance motor (SynRM) drives. The ADRC is a robust adaptive extension of the input-output feedback linearization control (FLC). It performs the exact linearization of the SynRM model by a suitable nonlinear transformation of the state based on the online estimation of the corrective term by the so-called extended state observers (ESO). Consequently, any unmodeled dynamics or uncertainty of the parameters are properly addressed. The control strategy has been verified successfully both in numerical simulations and experimentally on a suitably developed test set-up that provides the ADRC robustness versus parameters variations which cannot be obtained with other model-based nonlinear control techniques (e.g., FLC). Simulation results show the capability of the ADRC to maintain its dynamic performance, even in the presence of quick variations of the SynRM dynamic inductances. Experimental results confirm the robustness of the ADRC versus any model parameter uncertainty. The proposed ADRC has been experimentally compared with a previously developed FLC, in both a tuned and detuned working configuration, with the classic rotor oriented control, and with a finite state model predictive control (MPC), where speed control is integrated into the MPC. Experimental results show far better robustness versus any parameter variation.

In the midst of a global health crisis, it is of utmost importance for healthcare technologies to possess the capability to regulate and monitor the physiological variables of patients remotely and automatically. The effective control of mean arterial pressure (MAP) in a closed-loop manner is particularly critical for individuals who are critically ill or in the process of recovering from surgical procedures. Within the framework of the present research, an adaptive closed-loop structure has been formulated with the objective of controlling a patient’s MAP through governed administration of the medication sodium nitroprusside (SNP), to attain the desired MAP levels under varying conditions. The proposed closed-loop technique incorporates an intelligent controller known as the active disturbance rejection control (ADRC) with the intention of tracking the desired MAP value, alongside the utilization of continuous action policy gradient (CAPG) for the optimization of the controller’s coefficients. Under the DRL strategy, an actor is responsible for generating policy requests, while a critic assesses the efficacy of the actor’s policy directives. This approach uses gradient descent to train the weight values of both actor and critic networks, and it is dependent on the reward return linked to the MAP fault. Upon comparing the outcomes of the recommended structure with conventional models, numerical simulation results demonstrate the superiority of the proposed system in coping with varying working conditions, key-value fluctuations, and uncertainties, while effectively maintaining the desired mean arterial pressure and drug administration rate.

The availability and cost of fossil fuels, natural disasters, aging infrastructure, climate change, and rising electricity consumption have affected today’s power grids. One of the most practical solutions for achieving green and reliable energy is the use of microgrids. The stability of microgrids dominated by electronic converters presents several challenges. Among the problems encountered are the absence of physical inertia, delay in detecting islanding, and loss of stability associated with the transition between operating modes and variations of the load power. To overcome these challenges, this study presents a new robust control strategy based on active disturbance rejection control (ADRC). It is suitable for both islanded and connected operation modes with a single control, without an islanding detection algorithm or Phase-Locked Loop (PLL). The effectiveness of the control strategy is demonstrated through simulations and a comparative analysis with conventional droop control. Flexibility of the transition is also ensured. The proposed control strategy is successfully validated using a TI C2000 DSP TMS320F28335 microcontroller.

In the last decade, quadrotors have gained popularity among industry and academia due to their capabilities and the various applications in which they can be found. In addition to the above, because this is an underactuated system, researchers have found it a great challenge to control. Despite this, there is a wide variety of methodologies in the literature to control this type of system. Based on the above, this work proposed an alternative to trajectory tracking control for quadrotor unmanned aerial vehicles (UAV). The problem was divided into two main control loops: an outer control loop for the position coordinates, tackled through linear active disturbance rejection controllers (ADRC), and an inner control loop related to the orientation variables, addressed via robust proportional-integral-differential (PID) controllers. Furthermore, a generalized proportional integral observer (GPIO) was implemented to estimate the velocity and internal and external disturbances; therefore, the control strategy only depended on the attitude (position and orientation) quadrotor measurements. Then, the control performance was tested through numerical simulations and experimental tests, including wind disturbance inputs.

Improving tracking performance in speed controllers for permanent-magnet synchronous motor (PMSM) drive systems is critical due to internal challenges such as parameter variations, model uncertainty, and external disturbances like load changes. This paper proposes a new method that combines sensorless model predictive control (MPC) with active disturbance rejection control (ADRC), employing an extended state observer (ESO) as a key component of the ADRC. Notably, the proposed ADRC-MPC control integrates the advantages of MPC, such as good time response, high robustness against load variation, and a low effect of parameter variation in comparison to conventional control methods like field-oriented control (FOC). The ADRC-MPC reduces torque and flux ripples and also reduces torque and flux irregularities as well as current harmonics, which presents a major drawback in direct torque control (DTC). The proposed control with finite set model predictive control (FS-MPC) eliminates the PWM modulation and the complexity of continuous control set model predictive control (CCS-MPC). In the outer loop, the ADRC-MPC and the ESO present a very good solution. It presents a lower processing requirement than other controllers, especially the fuzzy logic controller (FLC), and also presents a consistent dynamic behavior across the entire operating range, contrary to the PID. The ADRC with ESO presents a promising solution to these challenges. The effectiveness of the proposed method is demonstrated through numerical simulations using MATLAB/Simulink software and experiments on a 3-kW surface-mounted PMSM drive system. both simulation and experimental results under different conditions show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, a control method of a full-bridge DC–DC converter for a pulse power supply with controllable charging time based on Active Disturbance Rejection Control (ADRC) is presented. For this application, the scheme objective is to achieve a flexible charging current to adjust the charging time of the pulse power supply. Due to the existence of switching devices in the system, the dynamic characteristics of the control system are complicated; an LADRC (Linear Active Disturbance Rejection Control) controller is constructed to regulate the charging of the converter current so as to improve the flexibility and dynamic performance of high-voltage pulse power supply. LADRC linearizes the extended state observer and links its parameters to the observer bandwidth to simplify the design of ESO. The proportional coefficient or differential coefficient is connected with the bandwidth of the controller to simplify its tuning, simplify the nonlinear function, more parameters, and complicated adjustment of the ADRC in practical application. The inner loop current regulator assembled is beneficial to the dynamic performance of the loop. The resulting double closed-loop structure improves steady-state and transient current-tracking performance. In addition, stability analysis of the proposed strategy is also performed. The proposed control approach is compared with PI. To verify the feasibility of the proposed scheme, an experimental prototype was constructed and tested to confirm the superiority of the proposed method in terms of dynamic performance. [ABSTRACT FROM AUTHOR]

The reaction flywheel is a crucial operational component within a satellite’s attitude control system. Enhancing the performance of the reaction flywheel speed control system holds significant importance for satellite attitude control. In this paper, an active disturbance rejection control (ADRC) approach is introduced to mitigate the impact of uncertain disturbances on reaction flywheel speed control precision. The reaction flywheel speed control system is designed as an ADRC controller due to the current challenge of measuring unknown disturbances accurately in the reaction flywheel system. To derive the rotor’s speed observation value and the estimated total disturbances value, the sampled data of the reaction flywheel rotor position and torque control signal are fed into the extended state observer. The estimated total disturbances value is compensated on feedforward control, which could mitigate significantly the effects of various nonlinear disturbances. The paper initially establishes the rationale behind the reaction flywheel ADRC controller through theoretical analysis, followed by analysis of the differences of performance of reaction flywheel control by the ADRC controller and the PID controller in MATLAB/SIMULINK. Simulation results demonstrate the evident advantages of the ADRC controller over the PID controller in terms of speed command tracking capability and disturbances suppression ability. Subsequently, the ADRC controller program and the PID controller program are implemented on the reaction flywheel control circuit, and experiments are conducted to contrast speed command tracking and disturbance suppression. Importantly, the experimental outcomes align with the simulation results.