DeepAI AI Chat
Log In Sign Up

ℒ_1Quad: ℒ_1 Adaptive Augmentation of Geometric Control for Agile Quadrotors with Performance Guarantees

by   Zhuohuan Wu, et al.

Quadrotors that can operate safely in the presence of imperfect model knowledge and external disturbances are crucial in safety-critical applications. We present L1Quad, a control architecture for quadrotors based on the L1 adaptive control. L1Quad enables safe tubes centered around a desired trajectory that the quadrotor is always guaranteed to remain inside. Our design applies to both the rotational and the translational dynamics of the quadrotor. We lump various types of uncertainties and disturbances as unknown nonlinear (time- and state-dependent) forces and moments. Without assuming or enforcing parametric structures, L1Quad can accurately estimate and compensate for these unknown forces and moments. Extensive experimental results demonstrate that L1Quad is able to significantly outperform baseline controllers under a variety of uncertainties with consistently small tracking errors.


page 4

page 10

page 12

page 13


Safe Feedback Motion Planning: A Contraction Theory and L_1-Adaptive Control Based Approach

Autonomous robots that are capable of operating safely in the presence o...

Performance, Precision, and Payloads: Adaptive Nonlinear MPC for Quadrotors

Agile quadrotor flight in challenging environments has the potential to ...

Adaptive Steering Control for Steer-by-Wire Systems

Steer-by-Wire (SBW) systems are being adapted widely in semi-autonomous ...

Adaptive Controllers for Quadrotors Carrying Unknown Payloads

With the advent of intelligent transport, quadrotors are becoming an att...

Bayesian Optimization-based Nonlinear Adaptive PID Controller Design for Robust Mobile Manipulation

In this paper, we propose to use a nonlinear adaptive PID controller to ...

Correct-by-Design Control of Parametric Stochastic Systems

This paper addresses the problem of computing controllers that are corre...