scholarly journals An error-based active disturbance rejection control with memory structure

2020 ◽  
pp. 002029402091521 ◽  
Author(s):  
Sen Chen ◽  
Zhixiang Chen ◽  
Zhiliang Zhao
Keyword(s):  
Disturbance Rejection ◽  
Reference Signal ◽  
Memory Structure ◽  
Necessary Condition ◽  
Control Input ◽  
Active Disturbance Rejection Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Input Gain ◽  
With Memory

The paper studies the control problem for nonlinear uncertain systems with the situation that only the current reference signal is available. By constructing a memory structure to save the previous reference signals, a novel error-based active disturbance rejection control with an approximation for the second-order derivative of reference signal is proposed. The transient performance of the proposed method is rigorously studied, which implies the high consistence of the closed-loop system. More importantly, to attain the satisfactory tracking performance, the necessary condition for nominal control input gain is quantitatively investigated. Furthermore, the superiority of the proposed method is illuminated by contrastively evaluating the sizes of the total disturbance and its derivative. The proposed method can alleviate the burden of the estimation and compensation for total disturbance. Finally, the experiment for a manipulator platform shows the effectiveness of the proposed method.

Motion-based active disturbance rejection control for a non-linear full-car suspension system

2017 ◽  
Vol 232 (5) ◽  
pp. 616-631 ◽  
Author(s):  
Panshuo Li ◽  
James Lam ◽  
Kie Chung Cheung
Keyword(s):  
Disturbance Rejection ◽  
Control Method ◽  
Reference Signal ◽  
Suspension System ◽  
Ride Quality ◽  
Active Disturbance Rejection Control ◽  
Active Disturbance Rejection ◽  
Car Suspension ◽  
Disturbance Rejection Control ◽  
Non Linear

This paper investigates the vibration attenuation problem of a non-linear full-car suspension system and aims to stabilize the vehicle attitude to provide a good ride quality. First, with respect to heave motion, pitch motion and roll motion, the full-car suspension system is separated into three interconnected subsystems. For each subsystem, corresponding motion-based controllers are designed to attenuate the vibrations of the sprung mass. A non-linear tracking differentiator is used to track the reference signal and to obtain its derivative. An extended state observer is established to estimate the total disturbance, which includes all the uncertainties and the external disturbance. Based on the principle of active disturbance rejection control, proportional–derivative and fuzzy proportional–derivative controllers are designed to control the resulting linear system with total disturbance compensation. Finally, four actuator forces are computed online using the three motion-based controllers obtained. Simulations are carried out in different road conditions; the results illustrate the merits of the proposed control method.

scholarly journals Active Disturbance Rejection Synchronization of Morris-Lecar Neurons

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Wei Wei ◽  
Yanjie Shao ◽  
Min Zuo
Keyword(s):  
Disturbance Rejection ◽  
Neural Model ◽  
Control Input ◽  
Active Disturbance Rejection Control ◽  
Neural Models ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Parameter Perturbations ◽  
Simulation Results ◽  
Difficult Issue

Synchronization of biological neurons is not only a hot topic, but also a difficult issue in the field of bioelectrical physiology. Numerous reported synchronization algorithms are designed on the basis of neural model, but they have deficiencies like relatively complex and poor robustness and are difficult to be realized. Morris-Lecar neuron is considered, and linear active disturbance rejection control (LADRC) is designed. Only one control input signal is utilized to synchronize membrane potentials of biological neurons. Meanwhile, in order to verify the robustness of synchronization, sinusoidal signal and parameter perturbations are introduced in numerical simulations. LADRC can still achieve satisfactory synchronization. Both theoretical and numerical simulation results show that LADRC is capable of estimating and cancelling disturbances and uncertainties. Neither accurate neural models nor concrete disturbance signal models are indispensable. A more practical and effective thought is provided to address the synchronization between neurons.

Practical control implementation of tri-tiltRotor flying wing unmanned aerial vehicles based upon active disturbance rejection control

2020 ◽  
Vol 234 (4) ◽  
pp. 943-960
Author(s):  
Zian Wang ◽  
Zheng Gong ◽  
Yongliang Chen ◽  
Mingwei Sun ◽  
Jinfa Xu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Flight Control ◽  
Disturbance Rejection ◽  
Effective Control ◽  
Control Input ◽  
Active Disturbance Rejection Control ◽  
Active Disturbance Rejection ◽  
Aerial Vehicles ◽  
Disturbance Rejection Control ◽  
Control Scheme

Tilt rotor unmanned aerial vehicles exhibit their effectiveness via a novel and convenient structure. However, the flight control system is a critical problem in need of a robust solution. Focusing on its flight features, which display strong nonlinear and varying dynamics, caused by complexity in the aerodynamic layout and tilting structure, a practical control scheme is proposed to meet such technical issues. This paper first develops the nonlinear model, consisting of the interference between rotors and the wing body, relying on wind tunnel technology. A simplified linear model that decomposes the longitudinal and lateral components is used in order to facilitate controller design. Then, a time-scale separation decoupling control scheme based upon active disturbance rejection control is proposed to cope with control challenges. Introducing the concept of virtual control input, an effective control allocation is obtained by choosing the appropriate bandwidth in the frequency domain. The extended state observer is applied to estimate and compensate for unknown total disturbances and model uncertainties. Finally, robustness verification, successful test-bench experiments, and practical flight tests that show the fast tracking and disturbance rejection of the active disturbance rejection control controller are discussed. The proposed practical coupling rejection control design demonstrates its capability to employ a single input single output method to control a tri-tiltRotor flying wing unmanned aerial vehicle relying on active disturbance rejection control.

scholarly journals U-Model-Based Active Disturbance Rejection Control for the Dissolved Oxygen in a Wastewater Treatment Process

2020 ◽  
Vol 2020 ◽  
pp. 1-14 ◽  
Author(s):  
Wei Wei ◽  
Nan Chen ◽  
Zhiyuan Zhang ◽  
Zaiwen Liu ◽  
Min Zuo
Keyword(s):  
Wastewater Treatment ◽  
System Dynamics ◽  
Disturbance Rejection ◽  
Control Input ◽  
Active Disturbance Rejection Control ◽  
Wastewater Treatment Process ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
System Output ◽  
Do Concentration

Dissolved oxygen (DO) concentration is a key variable in wastewater treatment process (WWTP). It directly influences effluent quality of a wastewater treatment. However, due to the great changes of the influent flow rate and the large uncertainties of the wastewater in composition, concentration, and temperature, most control approaches become powerless on DO regulation. To improve the robustness of a DO control, and reduce the phase delay between the control input and the system output, a U-model-based active disturbance rejection control (UADRC) is proposed. The U-model control (UC) reduces the phase delay between the control input and the system output. The active disturbance rejection control (ADRC) enhances the robustness of the closed-loop system. Also, ADRC converts the system dynamics to be integrators connected in series, which helps the realization of UC. By changing the system dynamics to be an approximate unit, a controller based on desired closed-loop system dynamics can be designed and the DO concentration is guaranteed. UADRC combines advantages of both UC and ADRC, and a commonly accepted benchmark simulation model no.1 (BSM1) is taken to verify the proposed UADRC. Numerical results show that, with similar energy consumption, the UADRC is able to achieve much better tracking performance than ADRC, SMC, and PI with suggested parameters.

scholarly journals Based on Robust Sliding Mode and Linear Active Disturbance Rejection Control for Attitude of Quadrotor Load UAV

2021 ◽  
Author(s):  
Zhaoji Wang ◽  
Tong Zhao
Keyword(s):  
Adaptive Control ◽  
Real Time ◽  
Disturbance Rejection ◽  
Control Method ◽  
Sliding Mode ◽  
Reference Signal ◽  
Active Disturbance Rejection Control ◽  
Mass Variation ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

Abstract In this paper, a mass adaptive control method combining robust sliding mode control (SMC) and linear active disturbance rejection control (LADRC) is designed for the quadrotor load unmanned aerial vehicle (UAV) with mass variation. The scheme combines the advantages of SMC and LADRC. SMC can enhance the robustness of the controller, improve the anti-disturbance performance and overcome the problem of low control precision caused by bandwidth limitation of LADRC. The linear extended state observer (LESO) can estimate the external and internal disturbances of the system in real time, and then compensate the total disturbance through the PD controller. In order to simplify parameter setting, adaptive control is introduced in LADRC to adjust controller parameters in real time. In addition, adaptive law is also used to control the mass variation of the quadrotor. Then the stability of the whole system is verified by Lyapunov stability theory. Finally, the comparison with LADRC shows the superiority of the designed scheme, which can track the reference signal stably and effectively.

scholarly journals Active disturbance rejection control for a piezoelectric nano-positioning system: A U-model approach

2021 ◽  
pp. 002029402110000
Author(s):  
Wei Wei ◽  
Bowen Duan ◽  
Min Zuo ◽  
Weicun Zhang
Keyword(s):  
Disturbance Rejection ◽  
Control Input ◽  
Phase Lag ◽  
Active Disturbance Rejection Control ◽  
Model Based ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Model Control ◽  
Key Issues ◽  
Speed And Accuracy

Both speed and accuracy are key issues in nano-positioning. However, hysteresis existing in piezoelectric actuators severely reduces the positioning speed and accuracy. In order to address the hysteresis, a U-model based active disturbance rejection control is proposed. Based on the linear active disturbance rejection control, a controlled plant is dynamically transformed to be pure integrators. Then, according to the U-model control, a common inversion is obtained and the controlled plant is converted to be “1.” By integrating advantages of both linear active disturbance rejection control and U-model control, the U-model based active disturbance rejection control does promote the reference tracking speed and accuracy. Stability and steady-state error of the close-loop system have been analyzed. Phase lag between the system output and the control input has been effectively eliminated, and the phase-leading advantage of the U-model based active disturbance rejection control has been confirmed. Experimental results show that the U-model based active disturbance rejection control is capable of achieving faster and more accurate positioning. Remarkable improvements and practical realization make the U-model based active disturbance rejection control more promising in nano-positioning.

Sign in / Sign up

Export Citation Format

Share Document