A Nonlinear UAV Control Tuning Under Communication Delay using HPC Strategies in Parameters Space

Abstract

In practical applications, the presence of delays can deteriorate the performance of the control system or even cause plant instability. However, by properly controlling these delays, it is possible to improve the performance of the mechanism. The present work is based on a proposal to analyze the asymptotic stability and convergence of a quadrotor robot, an unmanned aerial vehicle (UAV), on the performance of a given task, under time delay in the data flow. The effects of the communication delay problem, as well as the response-signal behavior of the quadrotors in the accomplishment of positioning mission are presented and analyzed from the insertion of fixed time delay intervals in the UAVs' data collected by its sensors system. Due to the large search space in the set of parameter combinations and the high computational cost required to perform such an analysis by sequentially executing thousands of simulations, this work proposes an open source GPU-based implementation to simulate the robot behavior. Experimental results show a speedup up to 4900x in comparison to MATLAB® implementation. The implement is available in Colab Google platform.

High‐performance graphics processing unit‐based strategy for tuning a unmanned aerial vehicle controller subject to time‐delay constraints

“…21 Recently, applications with robotics have been widely studied and implemented with Google Colab. 9 In summary, it provides a runtime fully configured for deep learning and free-of-charge access to a robust GPU. When initializing a session in Colab, the user has access to a dual-core processor, 12 GBytes of RAM and 40-50 MB of L3 cache.…”

“…This version was presented in the previous work. 9 In this work, the identification of possible bottlenecks in GPU code is analyzed. In the first optimization, manual code factoring is introduced.…”

“…As aforementioned, this is an extended version of our previous work. 9 Given a two-parameter design space, execution time is reduced by refactoring the code to optimize the use of the GPU register. The order of project exploration, MATLAB GPU support, and MATLAB C code generator is also explored.…”

Quadcopter Vehicle Proportional-Integral-Derivative Controller (PIDC) Tuning by Particle-Swarm Optimization (PSO)

“…Additionally, disregard scenarios in which the UAV fails to reach the point, is too slow to reach the point, or reaches the target location but oscillates with an undesired amplitude. Gain difference intervals were determined based on the investigated system's behavior and, more specifically, the controller's responses in order to minimize saturation of the control signals [15]. As a result, a PID with chose PSO-gain is used to adjust the quadrotor's closed-loop fast controls to reach the desired point.…”

“…As a result, a PID with chose PSO-gain is used to adjust the quadrotor's closed-loop fast controls to reach the desired point. PIDC is beneficial due to its simplicity and ease of implementation and takes the general mathematical form as in Equation 2,3 [15,16] (2)…”