An Efficient Real-Time NMPC for Quadrotor Position Control under Communication Time-Delay

TL;DR

This paper introduces a real-time NMPC-based position control system for quadrotors that effectively manages communication delays and actuator bounds, utilizing offboard computation and advanced optimization solvers for improved agility.

Contribution

It presents a novel offboard NMPC control architecture with delay compensation and bounds enforcement, optimized for limited onboard computational resources.

Findings

Achieved real-time control with solution times suitable for quadrotor operation.

Demonstrated effective handling of communication delays and actuator bounds.

Validated on Crazyflie 2.1 nano-quadrotor with successful position control.

Abstract

The advances in computer processor technology have enabled the application of nonlinear model predictive control (NMPC) to agile systems, such as quadrotors. These systems are characterized by their underactuation, nonlinearities, bounded inputs, and time-delays. Classical control solutions fall short in overcoming these difficulties and fully exploiting the capabilities offered by such platforms. This paper presents the design and implementation of an efficient position controller for quadrotors based on real-time NMPC with time-delay compensation and bounds enforcement on the actuators. To deal with the limited computational resources onboard, an offboard control architecture is proposed. It is implemented using the high-performance software package acados, which solves optimal control problems and implements a real-time iteration (RTI) variant of a sequential quadratic programming (SQP) scheme with Gauss-Newton Hessian approximation. The quadratic subproblems (QP) in the SQP scheme are solved with HPIPM, an interior-point method solver, built on top of the linear algebra library BLASFEO, finely tuned for multiple CPU architectures. Solution times are further reduced by reformulating the QPs using the efficient partial condensing algorithm implemented in HPIPM. We demonstrate the capabilities of our architecture using the Crazyflie 2.1 nano-quadrotor.