Litcius/Paper detail

Quadrotor Trajectory Control Based on Energy-Optimal Reference Generator

Domenico Bianchi, Alessandro Borri, Federico Cappuzzo, S. Di Gennaro

2024Drones18 citationsDOIOpen Access PDF

Abstract

Inspired by the limited battery life of multi-rotor unmanned aerial vehicles (UAVs), this research investigated hierarchical real-time control of UAVs with the generation of energy-optimal reference trajectories. The goal was to design a reference generator and controller based on optimal-control theory that would guarantee energy consumption close to optimal with lower computational cost. First, a least-squares-estimation-(LSE) algorithm identified the parameters of the UAV mathematical model. Then, by considering a precise electrical model for the brushless DC motors and rest-to-rest maneuvers, the extraction of clear rules to compute the optimal mission time and generate ’energetic trajectories’ was performed. These rules emerged from analyzing the optimal-control strategy results that minimized the consumption over many simulations. Afterward, a hierarchical controller tracked those desired energetic trajectories identified as sub-optimal. Numerical experiments compared the results regarding trajectory tracking, energy performance index, and battery state of charge (SOC). A co-simulation framework consisting of commercial software tools, Simcenter Amesim for the physical modeling of the UAV, and Matlab-Simulink executed numerical simulations of the implemented controller.

Topics & Concepts

Controller (irrigation)Optimal controlControl theory (sociology)TrajectoryComputer scienceMATLABEnergy consumptionRotor (electric)Control engineeringState of chargeEnergy (signal processing)Battery (electricity)Power (physics)Control (management)EngineeringMathematical optimizationMathematicsArtificial intelligenceBiologyAgronomyQuantum mechanicsOperating systemMechanical engineeringAstronomyStatisticsPhysicsElectrical engineeringAdaptive Control of Nonlinear SystemsRobotic Path Planning AlgorithmsAerospace Engineering and Control Systems