A comprehensive decoupling control strategy for a gas flow facility based on active disturbance rejection generalized predictive control

2018 ◽  
Vol 97 (3) ◽  
pp. 762-776 ◽  
Author(s):  
Xia Wu ◽  
Zengqiang Chen ◽  
Yue Zhao ◽  
Lijun Sun ◽  
Mingwei Sun
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Disturbance Rejection ◽  
Gas Flow ◽  
Decoupling Control ◽  
Generalized Predictive Control ◽  
Active Disturbance Rejection

scholarly journals A Control Method for IPMSM Based on Active Disturbance Rejection Control and Model Predictive Control

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 760
Author(s):  
Fang Liu ◽  
Haotian Li ◽  
Ling Liu ◽  
Runmin Zou ◽  
Kangzhi Liu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Duty Cycle ◽  
Control Strategy ◽  
Disturbance Rejection ◽  
Torque Ripple ◽  
Current Control ◽  
Active Disturbance Rejection Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

In this paper, the speed tracking problem of the interior permanent magnet synchronous motor (IPMSM) of an electric vehicle is studied. A cascade speed control strategy based on active disturbance rejection control (ADRC) and a current control strategy based on improved duty cycle finite control set model predictive control (FCSMPC) are proposed, both of which can reduce torque ripple and current ripple as well as the computational burden. First of all, in the linearization process, some nonlinear terms are added into the control signal for voltage compensation, which can reduce the order of the prediction model. Then, the dq-axis currents are selected by maximum torque per ampere (MTPA). Six virtual vectors are employed to FCSMPC, and a novel way to calculate the duty cycle is adopted. Finally, the simulation results show the validity and superiority of the proposed method.

Decoupling control of high-purity heat integrated distillation column process via active disturbance rejection control and nonlinear wave theory

2020 ◽  
Vol 42 (12) ◽  
pp. 2221-2233 ◽  
Author(s):  
Yun Cheng ◽  
Zengqiang Chen ◽  
Mingwei Sun ◽  
Qinglin Sun
Keyword(s):  
Nonlinear Wave ◽  
Control Strategy ◽  
High Purity ◽  
Disturbance Rejection ◽  
Distillation Column ◽  
Decoupling Control ◽  
Active Disturbance Rejection Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control ◽  
Control Scheme

Although the heat integrated distillation is an energy-efficient and environment-friendly separation technology, it has not been commercialized. One of the reasons is that the nonlinear dynamics and the interactions between various control loops have limited the performance of the traditional control strategy. To achieve a high-purity product concentration, a dynamic decoupling control strategy based on active disturbance rejection control (ADRC) is proposed. The effects of interactions, uncertainties and external disturbances can be estimated and rejected by using extended state observer. Considering the constraints on manipulated variables, an optimized ADRC is designed for the first-order system. Moreover, a concentration observer based on a nonlinear wave model is formulated to reduce the number of sensors. In the simulation research, the related internal model control (IMC), multi-loop ADRC and model predictive control (MPC) are compared with the proposed control scheme. The simulation results demonstrate the advantages of the proposed control scheme on tight control, decoupling performance and disturbance rejection for the high-purity heat integrated distillation column.

A lateral control strategy for unmanned ground vehicles with model predictive control and active disturbance rejection control

2021 ◽  
pp. 014233122110253
Author(s):  
Zhiqiang Zuo ◽  
Mengjia Yang ◽  
Haoyu Wang ◽  
Yijing Wang ◽  
Li Wang ◽  
...  
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Disturbance Rejection ◽  
State Observer ◽  
Extended State Observer ◽  
Ground Vehicles ◽  
Extended State ◽  
Lateral Control ◽  
Active Disturbance Rejection ◽  
Disturbance Rejection Control

This paper presents a lateral control strategy with kinematic state error model-based predictive control and extended state observer for unmanned ground vehicles. Firstly, we propose a circular arc prediction technique to calculate the state of the reference system. Then, inspired by the idea of active disturbance rejection control, an extended state observer is utilized to estimate the value of the total disturbance caused by modeling uncertainties, external disturbance, and other factors in order to compensate model error. Finally, we propose a lateral controller that combines model-based prediction with extended state observer through state feedback to achieve precise trajectory tracking. The performance of the proposed control strategy is demonstrated by a co-simulation between CarSim and MATLAB/Simulink.

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