An Improved Active Disturbance Rejection Control Method for a Deep-Sea Aquaculture Vessel

This paper presents an input prediction based active disturbance rejection control scheme for systems with time-delay. The new scheme is motivated by the principle of Smith-predictor and traditional active disturbance rejection control. In order to make the transitive relation between the virtual control input and actual output approach a pure inertial element, an input predictor is adopted. The approximate error forms part of total error as well as the internal uncertainties and external disturbances, which can be easily dealt by traditional active disturbance rejection controller. Numerical examples and simulations based on the fuel dynamics of a boiler turbine unit show the improvement of the new method.

Nowadays, Dynamic Positioning (DP) is applied to various tasks such as subsea pipeline laying and the requirements for the positioning performance in marine operations are higher and higher. The main objective of this paper is to design a DP controller based on the Active Disturbance Rejection Control (ADRC) to solve the problems of long response time, large overshoot and low positioning accuracy in ship positioning. Firstly, the mathematical models of the ship and environmental disturbances are established. Secondly, the basic principle of ADRC is described. Meanwhile, stability analysis of the control system is introduced. Thirdly, ADRC is improved by the fal function filter and phase prediction method which solve the problem of dither and phase delay in tracking differentiators. Finally, simulations are carried out to verify the performance of the designed ADRC and the improved ADRC. Several simulation results show that the designed ADRC can realize the fixed-point control of the ship, which effectively solves the problems of long response time, overshoot and positioning accuracy, and compared with the traditional ADRC, the improved ADRC can reduce the error of straight track control, which indicates that ADRC can meet the requirements for the positioning performance and has a strong application value.

Load Frequency Control (LFC) is critical for ensuring stable operation of power systems, especially under diverse operating conditions. Within the analyzed single-area power network, the area control error (ACE) has been effectively managed despite uncertainties in system dynamics and the presence of external disturbances. The most recent study on disturbance rejection mechanisms has revealed that Active Disturbance Rejection Control (ADRC) is an effective controller for controlling uncertainty in systems, whether the system is linear or nonlinear. The importance of the ADRC controller resides in its model-free nature, that requires little understanding of the system model. The extended state observer (ESO) facilitates continuous estimation and compensation for disturbances, whether originating within the system or from external environments. However, certain process disturbances, such as time-delay, makes ADRC controller design more difficult. A solution to this problem is to use a Disturbance Observer (DO) which improves system performance. This study presents a comparative analysis of six control strategies: General Active Disturbance Rejection Control (ADRC) Controller with neglected delay, Delayed Input ADRC Controller, Smith Predictor ADRC Controller (ADRC-SP), Disturbance Observer (DO), PID (Proportional plus Integral plus Derivative) Controller, and PI (Proportional plus Integral) Controller, for their effectiveness in LFC of a single-area power system. Controllers are evaluated based on key performance metrics such as settling time, rise time, overshoot, and Integral of Absolute Error (IAE) under three scenarios: step load change, variable wind speed penetration, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$12 ~\mathrm{m} / \mathrm{s}$</tex> constant wind speed penetration. The results highlight the superior performance of the Disturbance Observer in minimizing settling time, overshoot, and Integral Absolute Error (IAE), making it the most robust and efficient controller among the evaluated strategies.

PurposeSea Lion Optimization (SLnO) algorithm involves the ability of exploration and exploitation phases, and it is able to solve combinatorial optimization problems. For these reasons, it is considered a global optimizer. The scheduling operation is completed by imitating the hunting behavior of sea lions.Design/methodology/approachCloud computing (CC) is a type of distributed computing, contributory in a massive number of available resources and demands, and its goal is sharing the resources as services over the internet. Because of the optimal using of these services is everlasting challenge, the issue of task scheduling in CC is significant. In this paper, a task scheduling technique for CC based on SLnO and multiple-objective model are proposed. It enables decreasing in overall completion time, cost and power consumption; and maximizes the resources utilization. The simulation results on the tested data illustrated that the SLnO scheduler performed better performance than other state-of-the-art schedulers in terms of makespan, cost, energy consumption, resources utilization and degree of imbalance.FindingsThe performance of the SLnO, Vocalization of Whale Optimization Algorithm (VWOA), Whale Optimization Algorithm (WOA), Grey Wolf Optimization (GWO) and Round Robin (RR) algorithms for 100, 200, 300, 400 and 500 independent cloud tasks on 8, 16 and 32 VMs was evaluated. The results show that SLnO algorithm has better performance than VWOA, WOA, GWO and RR in terms of makespan and imbalance degree. In addition, SLnO exhausts less power than VWOA, WOA, GWO and RR. More precisely, SLnO conserves 5.6, 21.96, 22.7 and 73.98% energy compared to VWOA, WOA, GWO and RR mechanisms, respectively. On the other hand, SLnO algorithm shows better performance than the VWOA and other algorithms. The SLnO algorithm's overall execution cost of scheduling the cloud tasks is minimized by 20.62, 39.9, 42.44 and 46.9% compared with VWOA, WOA, GWO and RR algorithms, respectively. Finally, the SLnO algorithm's average resource utilization is increased by 6, 10, 11.8 and 31.8% compared with those of VWOA, WOA, GWO and RR mechanisms, respectively.Originality/valueTo the best of the authors’ knowledge, this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere.

In order to improve the grid-connected stability of wind power grid-connected inverter, solve the harmonic and resonance problems encountered at the grid-connected interface of inverter when the load jumps. An improved linear active disturbance rejection control strategy combined with active damping (ILADRC-AD) is designed. Firstly, the mathematical model of inductance-capacitance-inductance (LCL) inverter is established, and the principle of traditional third order active disturbance rejection controller is analyzed. Based on the idea of lead correction, an improved LADRC is designed by series lead correction links on the total disturbance channel of the linear extended state observer (LESO). Capacitive current feedback active damping is introduced in combination with improved LADRC to generate an ILADRC-AD control strategy. The stability and robustness of the system are effectively improved. Finally, the frequency characteristics of the ILADRC-AD inverter system are analyzed by frequency domain analysis method, and the MATLAB simulation comparison of improved control and traditional PI and LADRC the grid current waveform. The results show that the improved control not only has more stable grid-connected current, but also has fast dynamic response and strong harmonic suppression when the load fluctuates.

In permanent magnetic synchronous motor (PMSM) speed regulation system, the tracking performance and disturbance rejection property of the system are coupled when using conventional active disturbance rejection control (ADRC) controller, which complicates the parameter setting of the controller. A decoupled ADRC controller with position feedback is proposed in this paper. Extended state observer (ESO) is modified to make disturbance rejection property of the system independent of the proportional coefficient, which affects both the tracking performance and the disturbance rejection property in the conventional ADRC control system. Using the modified ESO, the tracking performance and disturbance rejection property can be adjusted by the proportional coefficient and the bandwidth of ESO respectively, thus simplifies the parameter setting of the controller. Extensive experiments are performed on dSPACE DS1103 to verify the validity and practicality of the proposed algorithm.

Quadrotor trajectory tracking and obstacle avoidance by chaotic grey wolf optimization-based active disturbance rejection control

The PID control strategy is usually used to control the motor in the electric servo loading system CESLS), however there are some nonlinear factors such as mechanism clearance and surplus torque in the loading process, the conventional PID control method can't guarantee the control performance and the loading accuracy of the ESLS. A position feed-forward compensation controller is introduced in the ESLS, and an outer loop active disturbance rejection control (ADRC) strategy is designed to eliminate position disturbance and surplus torque disturbance in this paper. The method of “observation + compensation” used in the outer loop ADRC controller is not only to suppress the surplus torque, but also to improve the steady-state performance of the ESLS. The simulation result shows that the electric servo loading system based on ADRC strategy can effectively improve the tracking accuracy of the ESLS and enhance the stability of the ESLS.

It is unquestionably difficult to achieve precise path-following control for a parafoil system while taking sideslip angle effect into account. To address this challenge and enhance the robustness and flexibility of tracking control, this study presents an improved active disturbance rejection control (IADRC) strategy for parafoil path following based on the surge-guided line-of-sight (SGLOS) guidance law and the multi-strategy marine predator algorithm (MSMPA) optimization. Firstly, a guidance law is designed that simultaneously utilizes surge speed and heading angle for guidance. Then, IADRC is devised to enhance stability by mitigating observational errors from the extended state observer using fal function filters and phase predictions for pre-smoothing sideslip angles as well as abrupt yaw angle fluctuations. Additionally, a controller parameter tuning approach based on the improved MSMPA is proposed. Finally, the simulation results show that this strategy could effectively overcome the influence of wind field disturbances and achieve accurate path following control. Compared with the traditional PID control and linear active disturbance rejection control (LADRC), this method has a higher tracking accuracy and better robustness.

SummaryThe search for an effective nature‐inspired optimization technique has certainly continued for decades. This work proposes a novel robust multi‐user detection algorithm based on Grey wolf optimization and differential evolution algorithm to overcome the problem of high bit error rate (BER) in multi‐user detection under an impulse noise environment. The simulation results show that the iteration times of the multi‐user detector based on the proposed algorithm is less than those of genetic algorithm, differential evolution algorithm, Grey wolf optimization algorithm, salp swarm algorithm, grasshopper optimisation algorithm, and whale optimization algorithm with the lowerst BER value.

Pulse detonation combustor (PDC) is promising in aerospace engines due to its pressure-gain nature, which is more efficient than Brayton cycle. Aiming at the modeling and controller design of PDC, this paper proposes a PDC modeling method. The comparison with the experimental data shows that the temperature rise time of the PDC model is shorter than that of experiment, while the error of the final temperature does not exceed 1%. Then, the nonlinear and disturbance of the model are concentrated into uncertain terms, and active disturbance rejection controller (ADRC) is used to estimate and compensate uncertainty through real-time input and output data. Finally, the performance of ADRC and PI controller are compared by simulation. The simulation results show that the control performance of the PI controller and the ADRC controller is similar at the design point, but the ADRC controller has stronger robustness when deviating from the design point, and can still quickly maintain PDC outlet temperature under disturbance.

For the purpose of realizing permanent magnet synchronous motor (PMSM) systems with strong robustness and smooth speed, the quasi-proportional-resonant (QPR) controller is combined with super-twisting extended state observer (STESO) in this paper. Although traditional active disturbance rejection control scheme generally selects a sufficiently large bandwidth of linear extended state observer (LESO) to enhance the time-varying disturbance rejection capacity, the bandwidth of LESO is limited by system stiffness. To solve this tough issue, the STESO using generalized super-twisting technique is developed to optimize the stability and anti-disturbance capacity of motor drive system. In addition, the QPR controller is combined with the proposed STESO to suppress the motor speed fluctuation. Experimental results show that the proposed STESO-based QPR control algorithm has satisfactory characteristics.

Due to the frequently changing working conditions and complex operating environment of electric vehicle permanent magnet synchronous motor(PMSM), the motor parameters change dramatically. However, the performance of the PI current regulator, which is the most widely used, is sensitive to motor parameters and has weak robustness, which will lead to the deterioration of motor control system performance. To address this problem, active disturbance rejection control (ADRC) technology is applied to the PMSM current loop control. Firstly, the traditional ADRC current regulator is designed, and the performance and parameter tuning laws of the extended state observer are analyzed by the method of frequency domain analysis. Then, the traditional ADRC algorithm is improved in three aspects: observation error compensation, utilization of model information and anti-windup. After that, simulations and bench test validation are performed. The simulation results show that the improved ADRC current regulator is more robust in the face of parameter changes. The torque step test results show that the improved ADRC current regulator has fast dynamic response without overshoot and has high robustness when the motor parameters change. The dynamic test results show that the improved ADRC current regulator has high robustness when the load, speed and motor parameters change, and the anti-windup measures designed can effectively overcome the integral saturation phenomenon.

Introduction: SEPIC converters are widely used in power electronics due to their ability to either step up or step down voltage levels. However, their nonlinear behavior and the presence of a right-half-plane zero make it difficult to design fast and stable controllers. This study analyzes the performance of three control strategies applied to a SEPIC converter: Active Disturbance Rejection Control (ADRC), Proportional–Integral (PI), and Proportional–Integral–Derivative (PID).Objectives: to compare the reference tracking capability, disturbance rejection, and implementation complexity of ADRC, PI, and PID controllers applied to a SEPIC DC-DC converter.Materials and Methods: simulations were conducted in MATLAB/Simulink by introducing perturbations in both the power source and the output voltage. The performance indices IAE, ITAE, ISE, and ITSE were computed to quantify accuracy, speed, and robustness. The influence of ADRC tuning parameters, such as observer bandwidth and tracking differentiator speed, was also analyzed.Results: the ADRC controller exhibited the fastest response and best disturbance rejection, although it showed inherent oscillations and higher design complexity. The PI controller achieved a good balance between simplicity and performance, while the PID controller displayed the slowest response but smoother behavior under disturbances.Conclusions: ADRC is suitable for applications requiring fast and robust control performance. However, PI and PID controllers remain valid alternatives when simplicity or smoother control signals are prioritized.

This paper presents a high-precision control scheme based on active disturbance rejection control (ADRC) to improve the stabilization accuracy of an inertially stabilized platform (ISP) for aerial remote sensing applications. The ADRC controller is designed to suppress the effects of the disturbance on the stabilization accuracy that consists of a tracking differentiator, a nonlinear state error feedback, and an extended state observer. By the ADRC controller, the effects of both the internal uncertain dynamics and the external multisource disturbances on the system output are compensated as a total disturbance in real time. The disturbance rejection ability of the ADRC is analyzed by simulations. To verify the method, the experiments are conducted. The results show that compared with the conventional PID controller, the ADRC has excellent capability in disturbance rejection, by which the effect of main friction disturbance on the control system can be weakened seriously and the stabilization accuracy of the ISP is improved significantly.