A Comparative Study for Control of Quadrotor UAVs

Abstract

Modeling and controlling highly nonlinear, multivariable, unstable, coupled and underactuated systems are challenging problems to which a unique solution does not exist. Modeling and control of Unmanned Aerial Vehicles (UAVs) with four rotors fall into that category of problems. In this paper, a nonlinear quadrotor UAV dynamical model is developed with the Newton–Euler method, and a control architecture is proposed for 3D trajectory tracking. The controller design is decoupled into two parts: an inner loop for attitude stabilization and an outer loop for trajectory tracking. A few attitude stabilization methods are discussed, implemented and compared, considering the following control approaches: Proportional–Integral–Derivative (PID), Linear–Quadratic Regulator (LQR), Model Predictive Control (MPC), Feedback Linearization (FL) and Sliding Mode Control (SMC). This paper is intended to serve as a guideline work for selecting quadcopters’ control strategies, both in terms of quantitative and qualitative considerations. PID and LQR controllers are designed, exploiting the model linearized about the hovering condition, while MPC, FL and SMC directly exploit the nonlinear model, with minor simplifications. The fast dynamics ensured by the SMC-based controller together with its robustness and the limited estimated command effort of the controller make it the most promising controller for quadrotor attitude stabilization. The outer loop consists of three independent PID controllers: one for altitude control and the other two, together with a dynamics’ inversion, are entitled to the computation of the reference attitude for the inner loop. The capability of the controlled closed-loop system of executing complex trajectories is demonstrated by means of simulations in MATLAB/Simulink®.

Modeling and simulation of hit accuracy of EFP destruction element under disturbance conditions of UAV

“…During the terminal attack process, it is not possible for the UAV body to maintain a stable hovering attitude consistently [8][9]. The disturbances in the motion of the rotary-wing unmanned drone occur in space, and there is coupling between its longitudinal and lateral motion parameters.…”

Adaptive PID Control via Sliding Mode for Position Tracking of Quadrotor MAV: Simulation and Real-Time Experiment Evaluation

“…As a result, it is crucial to develop a reliable controller for the successful operation of MAVs, enabling researchers to evaluate and verify various approaches. To this end, a wide range of control strategies [1,2] have been explored, namely Proportional-Integral-Derivative (PID), Linear Quadratic Regulator (LQR), Backstepping, Feedback Linearization Control (FLC), Sliding Mode Control (SMC), Model Predictive Control (MPC), Neural Network, H-infinity, Fuzzy Logic, and Adaptive Control.…”

Adaptive Modified RISE-based Quadrotor Trajectory Tracking with Actuator Uncertainty Compensation

“…Developing reliable and safe control algorithms is still a challenging task in a myraid of quadrotor control applications [3]. Over the last decade several methods have been proposed to compensate for uncertain and time-varying external operating conditions; however, there remain numerous open challenges in the design of robust and adaptive nonlinear quadrotor UAV control systems, which are rigorously proven to simultaneously compensate for external disturbances (e.g., due wind gusts and aerodynamic anomalies) and internal anomalies, disturbances, and unmodeled effects in the UAV actuation dynamics (e.g., due to electromechanical propeller motor dynamics and/or actuator faults).…”

“…1 Krishna Bhavithavya Kidambi is an Assistant Professor in the Department of Mechanical and Aerospace Engineering, University of Dayton, Dayton, OH 45469. kkidambi1@udayton.edu 2 Madhur Tiwari is an Assistant Professor in the Department of Aerospace, Physics and Space Sciences, Florida Institute of Technology, Melbourne, FL 32901. mtiwari1@fit.edu 3 Emmanuel Ogbanje Ijoga, William MacKunis are with Physical Sciences Department, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114. ijogae@my.erau.edu, mackuniw@erau.edu Numerous recent approaches to quadrotor control are based on classical control methods applied to linearized models of the UAV dynamics [4], [5], [6], [7]. Popular linear control methods include proportional-integral-derivative (PID) control [6] and linear quadratic regulators (LQR) [7].…”