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 Disturbance rejection control for a wastewater treatment process by a learning approach

2020 ◽  
pp. 002029402095249
Author(s):  
Wei Wei ◽  
Nan Chen ◽  
Zaiwen Liu ◽  
Min Zuo
Keyword(s):  
Wastewater Treatment ◽  
Disturbance Rejection ◽  
Treatment Process ◽  
Learning Strategy ◽  
Iterative Learning ◽  
Active Disturbance Rejection Control ◽  
Wastewater Treatment Process ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Do Concentration

Nonlinearities, uncertainties and external disturbances commonly exist in a wastewater treatment process (WWTP). Those issues present great challenges to the control of the dissolved oxygen (DO) concentration in a WWTP. In this paper, an active disturbance rejection control (ADRC) is utilized to estimate the total disturbance and drive the DO concentration to track the set-value. Simultaneously, an iterative learning strategy is employed to adjust the parameters of an extended state observer (ESO) to improve the accuracy of the estimation and reduce the dependence on experience in determining parameters. By combining the advantages of the ADRC and the iterative learning strategy, an iterative learning based active disturbance rejection control (ILADRC) is constructed, and the close-loop stability is analyzed. The benchmark simulation model No.1 (BSM1) is utilized to confirm the ILADRC. Numerical results show that the ILADRC is more effective in the DO concentration control.

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.

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 Linear Active Disturbance Rejection Control of Dissolved Oxygen Concentration Based on Benchmark Simulation Model Number 1

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaoyi Wang ◽  
Fan Wang ◽  
Wei Wei
Keyword(s):  
Wastewater Treatment ◽  
Dissolved Oxygen ◽  
Simulation Model ◽  
Oxygen Concentration ◽  
Disturbance Rejection ◽  
Active Disturbance Rejection Control ◽  
Dissolved Oxygen Concentration ◽  
Tracking Accuracy ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

In wastewater treatment plants (WWTPs), the dissolved oxygen is the key variable to be controlled in bioreactors. In this paper, linear active disturbance rejection control (LADRC) is utilized to track the dissolved oxygen concentration based on benchmark simulation model number 1 (BSM1). Optimal LADRC parameters tuning approach for wastewater treatment processes is obtained by analyzing and simulations on BSM1. Moreover, by analyzing the estimation capacity of linear extended state observer (LESO) in the control of dissolved oxygen, the parameter range of LESO is acquired, which is a valuable guidance for parameter tuning in simulation and even in practice. The simulation results show that LADRC can overcome the disturbance existing in the control of wastewater and improve the tracking accuracy of dissolved oxygen. LADRC provides another practical solution to the control of WWTPs.

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.

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