Nonlinear PID-Type Controller for Quadrotor Trajectory Tracking

Moreno–Valenzuela, Javier; Pérez-Alcocer, Ricardo; Guerrero-Medina, Manuel; Dzul, A.

doi:10.1109/tmech.2018.2855161

Cited by 119 publications

(58 citation statements)

References 37 publications

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“…On the other hand, most high-level applications of SUAV systems require the vehicle to be able to track position commands in space or maintain static positions. Therefore, it is necessary to validate the attitude and altitude controller proposed in this paper by adding an external control loop (38) for the horizontal position of the system. As shown in Figure 13, the closed-loop system resultant gets a satisfactory tracking of the setpoints demanded by the positions (x E , y E , z E ).…”

Section: Resultsmentioning

confidence: 99%

“…The blocks indicated as Filters correspond to first order low-pass filters used for smoothing the set-point changes sent to the controllers. Equation (38) shows the control laws generated by the PIDs with filter to derivative action, employing the Laplace transform notation. Controllers parameters have been obtained experimentally, and are given in Table 3 (the negative sign is due to the sign criteria used for φ and y B , see Figure 2).…”

Section: Horizontal Position Controllermentioning

confidence: 99%

“…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.Kalman filters (KF) [6,16,22,23], extended Kalman filters (EKF) [21][22][23][24] and complementary filters [4,25] among others.Several methods have been published to control the fly of SUAV [1,2,5,[9][10][11]13,17,[26][27][28][29][30][31][32][33][34][35][36][37][38][39], of which [17,30,31,33,[35][36][37][38][39] use PID (Proportional Integral Derivative) controllers for attitude, altitude and/or horizontal position. However, as MIMO (Multiple-input Multiple-output) systems, the tuning of PID controllers for multi-rotor vehicles is not an easy issue.…”

mentioning

confidence: 99%

“…Several methods have been published to control the fly of SUAV [1,2,5,[9][10][11]13,17,[26][27][28][29][30][31][32][33][34][35][36][37][38][39], of which [17,30,31,33,[35][36][37][38][39] use PID (Proportional Integral Derivative) controllers for attitude, altitude and/or horizontal position. However, as MIMO (Multiple-input Multiple-output) systems, the tuning of PID controllers for multi-rotor vehicles is not an easy issue.…”

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confidence: 99%

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

2019

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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.

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Section: Resultsmentioning

confidence: 99%

Section: Horizontal Position Controllermentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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

2019

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“…Recently, considerable research has been devoted to the quadrotor as a certain kind of UAVs. Among various factors, station keeping, attitude control, and path tracking of quadrotors are of great importance [4].…”

Section: Introductionmentioning

confidence: 99%

Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks

Khosravian

Maghsoudi

2019

IJE

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A B S T R A C TDuring recent years there has been growing interest in unmanned aerial vehicles (UAVs). Moreover, the necessity to control and navigate these vehicles has attracted much attention from researchers in this field. T his is mostly due to the fact that the interactions between turbulent airflows apply complex aerodynamic forces to the system. Since the dynamics of a quadrotor are non-linear and the system is a multivariable one, moreover, it has six degrees of freedom for only four control inputs, then it is an under actuated system. T his is why conventional control algorithms employed to track desired trajectories of fully actuated aerial vehicles are no longer applicable for quadrotors. The main step in the manufacturing of a fully autonomous unmanned aerial vehicle is to design a controller which stabilizes the aerial vehicle in the presence of uncertainties and disturbances, then navigate it along a desired trajectory. T he aim of this study is to design and implement an intelligent controller for station keeping, attitude control, and path tracking of a quadrotor. For this purpose, an artificial neural network method was employed. The artificial neural network is one of the most powerful and useful tools in the modification of a control system. In this study, the control methods conventionally applied to quadrotors are reviewed at first. T hen, in order to analyze the behavior of the system and also to design the controller, the state equations of a quadrotor are discussed. Following that , the design of a recurrent neural network based non-linear PID control algorithm is presented. Finally, the results of the simulation performed are presented, and the performance of the proposed algorithm are investigated. It was shown that by using the proposed algorithm, the quadrotor tracks the desired trajectory, and simultaneously, its attitude is stabilized.

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Adaptive finite‐time attitude tracking control of quadrotor under actuator faults and external disturbances with guaranteed performance

Xia

Zhai

et al. 2022

Adaptive Control & Signal

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Summary The problem of attitude tracking control for quadrotor in presence of actuator faults and external disturbances is investigated in this article. By using fast terminal sliding mode control combined with prescribed performance technique, an adaptive control strategy capable of accommodating actuator faults and suppressing external disturbances is designed to achieve attitude finite‐time tracking control with guaranteed performance. In particular, with the help of Nussbaum functions, actuator faults are passively handled without extra development of fault detection and diagnosis mechanism. The finite‐time stability of attitude system under actuator faults and external disturbances is analyzed by Lyapunov stability criterion. Moreover, in order to demonstrate the effectiveness and superiority of proposed control scheme, numerical simulations in different cases are performed and presented in simulation section.

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Nonlinear PID-Type Controller for Quadrotor Trajectory Tracking

Cited by 119 publications

References 37 publications

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

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

Design of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks

Adaptive finite‐time attitude tracking control of quadrotor under actuator faults and external disturbances with guaranteed performance

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