scholarly journals MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

2019 ◽  
Author(s):  
Rafael Guardeño ◽  
Manuel J. López ◽  
Víctor M. Sánchez
Keyword(s):  
Pid Controller ◽  
Low Cost ◽  
Parametric Uncertainty ◽  
Estimation Errors ◽  
Plant Model ◽  
Tuning Method ◽  
Bias Drift ◽  
Noise Characteristics ◽  
Pid Controller Tuning ◽  
Mems Technology

In this work a new pre-tuning multivariable PID controllers method for quadrotors is put forward. A procedure based on LQR/LQG theory is proposed for attitude and altitude control. With the aim of analyzing performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, togheter with sensors drift/bias properties and noise characteristics of low-cost comercial sensors typically used in this type of applications (such as MARG with MEMS technology and LIDAR) are considered. In order to estimate the state vector and compensate bias/drift effects on rate gyros of the MARG, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robutsness analysis of the control system is carried out by means of numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show that the proposed pre-tuning method for multivariable PID controller is robust with respect to: a) parametric uncertainty in the plant model, b) disturbances acting at the plant input, c) sensors measurement and estimation errors.

scholarly journals MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

Robotics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 36 ◽  
Author(s):  
Rafael Guardeño ◽  
Manuel J. López ◽  
Víctor M. Sánchez
Keyword(s):  
Pid Controller ◽  
Controller Design ◽  
Low Cost ◽  
Robustness Analysis ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Estimation Errors ◽  
Plant Model ◽  
Bias Drift ◽  
Noise Characteristics

In this work, a new pre-tuning multivariable PID (Proportional Integral Derivative) controllers method for quadrotors is put forward. A procedure based on LQR/LQG (Linear Quadratic Regulator/Gaussian) theory is proposed for attitude and altitude control, which suposes a considerable simplification of the design problem due to only one pretuning parameter being used. With the aim to analyze the performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, together with sensors drift/bias properties and noise characteristics of low-cost commercial sensors typically used in this type of applications are considered. In order to estimate the state vector and compensate bias/drift effects in the measures, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design method for multivariable PID controller is robust with respect to: (a) parametric uncertainty in the plant model, (b) disturbances acting at the plant input, (c) sensors measurement and estimation errors.

A new PID controller tuning method based on multiple integrations

1999 ◽  
Vol 7 (5) ◽  
pp. 623-633 ◽  
Author(s):  
Damir Vrančić ◽  
Youbin Peng ◽  
Stanko Strmčnik
Keyword(s):  
Pid Controller ◽  
Controller Tuning ◽  
Tuning Method ◽  
Pid Controller Tuning

scholarly journals PID Controller Tuning using ACO Algorithm for AVR Systems

2020 ◽  
Vol 9 (3) ◽  
pp. 560-563 ◽  
Keyword(s):  
Pid Controller ◽  
Optimization Technique ◽  
Step Response ◽  
Pid Controllers ◽  
Tuning Method ◽  
Avr System ◽  
Disturbance Response ◽  
Pid Controller Tuning ◽  
Control Response ◽  
Optimal Gains

This paper features an effective technique to device the parameters of PID controllers for utilization together with an Automatic Voltage Regulator System (AVR). The quintessential goal is to acquire a good load disturbance response by minimizing the performance index/(Integral time square error). Simultaneously, the transient response is assured by limiting maximum overshoot, settling time and rise time of the step response to minimal values. For achieving these goals, optimum and quick tuning of the parameters (Kp, Ki, and Kd) is essential. In an effort to accomplish the aforementioned, the paper put forth an algorithm developed based on the Ant Colony Optimization technique (ACO) to decide optimal gains of PID controller and for getting optimal performance within an AVR system. Simulation results establish superior control response may be accomplished in comparison with methods like conventional tuning method (trial and error) and built-in genetic algorithm (GA) took-kit.e.

Digital Twin-Driven Controller Tuning Method for Dynamics

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Bin He ◽  
Tengyu Li ◽  
Jinglong Xiao
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Parameter Tuning ◽  
Control Effect ◽  
Controller Tuning ◽  
Digital Twin ◽  
Tuning Method ◽  
Twin Model ◽  
Pid Controller Tuning ◽  
Self Tuning

Abstract The control performance of the control system directly affects the running performance of the product. In order to solve the problem that the dynamics characteristics of mechanical systems are affected by the performance degradation of the controller, a digital twin-driven proportion integration differentiation (PID) controller tuning method for dynamics is proposed. In this paper, first, the structure and operation mechanism of the digital twin model for PID controller tuning are described. Using the advantages of virtual real mapping and data fusion of the digital twin model, combined with the online identification of the controlled object model, the problems of real-time feedback of an actual control effect of the controller and the unreal virtual model of the control system caused by time-varying working conditions are effectively solved, and the closed-loop self-tuning of PID controller is realized. At the same time, intelligent optimization algorithm is integrated to improve the efficiency and accuracy of PID controller parameter tuning. Second, the modeling method of the digital twin model is described from three aspects of physical prototyping, twin service system, and virtual prototyping. Finally, the controller tuning for gear transmission stability is taken as an example to verify the practicability of the proposed method.

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