Fuzzy self-adaptive PID control in actuator control system of unmanned aerial vehicle

2011 ◽  
Author(s):  
Jun Xiao ◽  
Weiwei Zhang ◽  
Yujie Han ◽  
Zhihua Dong
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Pid Control ◽  
Aerial Vehicle ◽  
Actuator Control ◽  
Adaptive Pid Control ◽  
Self Adaptive

scholarly journals Study on Fuzzy Self-Adaptive PID Control System of Biomass Boiler Drum Water

2013 ◽  
Vol 03 (01) ◽  
pp. 93-98 ◽  
Author(s):  
Junran Jin ◽  
Hengshuo Huang ◽  
Junman Sun ◽  
Yongchao Pang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Biomass Boiler ◽  
Boiler Drum ◽  
Adaptive Pid Control ◽  
Self Adaptive

Trajectory Tracking Control of Mobile Robot Based on Self-Adaptive PID Combined with Preview and Fuzzy Logic

2012 ◽  
Vol 590 ◽  
pp. 268-271 ◽  
Author(s):  
Da Lei Li ◽  
Zhan Shu He ◽  
Yue Feng Yin
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Mobile Robot ◽  
Trajectory Tracking ◽  
Pid Control ◽  
Tracking Control ◽  
Control Method ◽  
Trajectory Tracking Control ◽  
Adaptive Pid Control ◽  
Self Adaptive

A new method for controlling the steering and trajectory of the electric mobile robot is proposed. In order to control the robot’s position and heading, the path error and the heading error of the robot are taken into the control closed loop. On the basis of the self-adaptive PID control method combined with preview theory and fuzzy logic, a trajectory tracking control system is designed. Finally, experiments and simulation are conducted to test the control system. Both experimental and simulation results show that the mobile robot can approach the target trajectory quickly and then move along it, which confirm the validity and the efficiency of the trajectory tracking control system.

scholarly journals Penerapan Sistem Kendali PID pada Antena Pendeteksi Koordinat Posisi UAV

2015 ◽  
Vol 5 (2) ◽  
pp. 187
Author(s):  
Mahendra Budi Nugraha ◽  
Raden Sumiharto
Keyword(s):  
Control System ◽  
Motion Control ◽  
Unmanned Aerial Vehicle ◽  
Pid Control ◽  
Pid Controller ◽  
Vertical Motion ◽  
Pd Control ◽  
Is Implementation ◽  
Aerial Vehicle ◽  
Control Set

AbstrakPada penelitian ini telah diterapkan sebuah sistem kendali Proporsional-Integral-Derivatif (PID) pada antena pendeteksi koordinat posisi pesawat udara tanpa awak. Sistem kendali PID pada antena pendeteksi digunakan pada kendali gerak horizontal dan vertikal. Nilai acuan kendali PID untuk gerak horizontal adalah sudut azimuth antara antena dan UAV. Sudut tersebut didapatkan dari metode azimuth antara dua buah titik koordinat. Nilai acuan kendali PID untuk gerak vertikal adalah sudut elevasi yang didapat dari metode Haversine Formula dan Sinus Trigonemetri antara jarak dua titik koordinat terhadap ketinggian UAV. Metode tuning PID yang digunakan untuk memperoleh konstanta pengendali PID adalah metode Ziegler-Nichols dengan metode osilasi dan tabel penalaran sistem kendali Ziegler-Nichols.Hasil yang diperoleh dari penelitian ini berupa penerapan sistem kendali PID berdasarkan metode Ziegler-Nichols. Sistem kendali berdasarkan tabel penalaran Ziegler-Nichols divariasikan tiga jenis sistem kendali yaitu P, PI, dan PID. Sistem kendali PD juga diterapkan berdasarkan tabel penalaran Ziegler-Nichols dengan  pengendali integral diatur bernilai 0. Sistem kendali yang memiliki respon paling baik adalah sistem kendali PD dengan nilai Kp = 11,375 dan Kd = 0,372531 untuk kendali azimuth sedangkan kendali elevasi pada nilai Kp = 3,41 dan Kd = 0,111464. Respon yang dihasilkan kendali azimuth sebesar 0,32 detik dan kendali elevasi sebesar 0,34 detik. Kata kunci—PID, Antena Pendeteksi, Servo, UAV  Abstract In this project has been implemented a PID control system on antenna tracker of unmanned aerial vehicle coordinates. PID control system on antena tracker to be used on horizontal and vertikal motion control. The setpoint of PID controller for horizontal motion is azimuth’s angle between antenna and UAV. The angle produced by azimuth’s method between two coordinates. The setpoint of PID controller for vertical motion is elevasi’s angle that produced by haversine-formula’s method and Sinus Trigonometry between distance two coordinates toward altitude of UAV. Tuning of PID controller was calculated by Ziegler-Nichols’s method with oscillation’s method and reasoning table of Ziegler-Nichols.The result from this project is implementation PID control system with Ziegler-Nichols’s method. There ara 3 variations in Ziegler-Nichols’s table, that are P, PI, and PID control system. The PD control system also implemented with integral’s control set on 0. The control system that has a good response is PD control system with Kp = 11,375 and Kd = 0,372531 on azimuth’s control whereas elevasi’s control with Kp = 3,41 and Kd = 0,111464. Response that produced by azimuth’s control is 0,32 second and elevasi’s control is 0,34 second. Keywords—PID, Antenna Tracker, Servo, UAV 

The Application of Adaptive Fuzzy PID in the Liquid Level Cascade Control System

2013 ◽  
Vol 846-847 ◽  
pp. 321-324 ◽  
Author(s):  
Le Peng Song ◽  
Hua Bin Wang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Cascade Control ◽  
Liquid Level ◽  
Water Tank ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Cascade Control System ◽  
Self Adaptive

As liquid level cascade system has the character the issue of non-linearity ,time variability and the overshoot,tradition PID control can not meet the requirement of precise molding system. So devise a self-_ adaptive fuzzy PID control .A self-_ adaptive fuzzy PID control combined PID to control calculate way and faintness to control the advantage of method, this text permits water tank to carry on mathematics model to design the double permit a water tank liquid misty PID string class control system. Matlab/Simulink and fuzzy logic toolbox are simulated to the single loop PID control system,the cascade control system and the cascade control system based on fuzzy self-tuning PID were simulated with Simulink. The analysis and simulation results indicate that the character issue of non-linearity ,time variability and the overshoot of the liquid level cascade control system based on a self-_ adaptive fuzzy PID controller are superior to previous of two methods.

Modeling and control of a quadrotor tail-sitter unmanned aerial vehicles

2021 ◽  
pp. 095965182110504
Author(s):  
Hongbo Xin ◽  
Yujie Wang ◽  
Xianzhong Gao ◽  
Qingyang Chen ◽  
Bingjie Zhu ◽  
...  
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Euler Angle ◽  
Level Flight ◽  
Aerial Vehicles ◽  
Flight Mode ◽  
Aerial Vehicle ◽  
Hover Flight ◽  
And Control

The tail-sitter unmanned aerial vehicles have the advantages of multi-rotors and fixed-wing aircrafts, such as vertical takeoff and landing, long endurance and high-speed cruise. These make the tail-sitter unmanned aerial vehicle capable for special tasks in complex environments. In this article, we present the modeling and the control system design for a quadrotor tail-sitter unmanned aerial vehicle whose main structure consists of a traditional quadrotor with four wings fixed on the four rotor arms. The key point of the control system is the transition process between hover flight mode and level flight mode. However, the normal Euler angle representation cannot tackle both of the hover and level flight modes because of the singularity when pitch angle tends to [Formula: see text]. The dual-Euler method using two Euler-angle representations in two body-fixed coordinate frames is presented to couple with this problem, which gives continuous attitude representation throughout the whole flight envelope. The control system is divided into hover and level controllers to adapt to the two different flight modes. The nonlinear dynamic inverse method is employed to realize fuselage rotation and attitude stabilization. In guidance control, the vector field method is used in level flight guidance logic, and the quadrotor guidance method is used in hover flight mode. The framework of the whole system is established by MATLAB and Simulink, and the effectiveness of the guidance and control algorithms are verified by simulation. Finally, the flight test of the prototype shows the feasibility of the whole system.

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