The Model Reference Adaptive Control Method for Pesticide Spraying Quadrotor UAVs

2021 ◽  
pp. 5007-5016
Author(s):  
Xusheng Lei ◽  
Shigang Liao ◽  
Yankun Hao
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Model Reference Adaptive Control ◽  
Model Reference ◽  
Quadrotor Uavs ◽  
Model Reference Adaptive

Model Reference Adaptive Control Based on KP Model for Magnetically Controlled Shape Memory Alloy Actuators

2017 ◽  
Vol 15 (1_suppl) ◽  
pp. 31-37 ◽  
Author(s):  
Miaolei Zhou ◽  
Yannan Zhang ◽  
Kun Ji ◽  
Dong Zhu
Keyword(s):  
Adaptive Control ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Control Method ◽  
Model Reference Adaptive Control ◽  
Positioning Accuracy ◽  
Model Reference ◽  
Hysteresis Nonlinearity ◽  
Adopted Model ◽  
Model Reference Adaptive

Introduction Magnetically controlled shape memory alloy (MSMA) actuators take advantages of their large deformation and high controllability. However, the intricate hysteresis nonlinearity often results in low positioning accuracy and slow actuator response. Methods In this paper, a modified Krasnosel'skii-Pokrovskii model was adopted to describe the complicated hysteresis phenomenon in the MSMA actuators. Adaptive recursive algorithm was employed to identify the density parameters of the adopted model. Subsequently, to further eliminate the hysteresis nonlinearity and improve the positioning accuracy, the model reference adaptive control method was proposed to optimize the model and inverse model compensation. Results The simulation experiments show that the model reference adaptive control adopted in the paper significantly improves the control precision of the actuators, with a maximum tracking error of 0.0072 mm. Conclusions The results prove that the model reference adaptive control method is efficient to eliminate hysteresis nonlinearity and achieves a higher positioning accuracy of the MSMA actuators.

scholarly journals Multivariable Model Reference Adaptive Control of an Industrial Power Boiler Using Recurrent RBFN

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jafar Tavoosi ◽  
Yavar Azarakhsh ◽  
Ardashir Mohammadzadeh ◽  
Saleh Mobayen ◽  
Jihad H. Asad ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Steam Pressure ◽  
Model Reference Adaptive Control ◽  
Operating Pressure ◽  
Model Reference ◽  
Precise Control ◽  
Model Reference Adaptive ◽  
Power Boiler

In industrial steam systems, the process requires a specific pressure, and the maximum permissible operating pressure is different. If the inlet steam pressure to the steam consuming equipment exceeds the operating pressure, it may cause hazards. Therefore, the more precise control of the boiler pressure is important. Since we are dealing with a nonlinear, time-varying, and multivariable system, the control method must be designed to handle this system well. Most of the methods proposed so far are either not physically feasible or the system has considered very simple. Therefore, in this paper, while modeling the boiler and its pressure relations more precisely, we will introduce a recurrent type-2 fuzzy RBFN-based model reference adaptive control system with various uncertainties so that the uncertainty and inaccuracy of the model can be compensated. The experimental results prove the efficiency of the proposed method in boiler control.

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