Allowing for a “virtual” full actuation of a rotary inverted pendulum (RIP) system with only a single physical actuator has been a challenging problem. In this paper, a hybrid control scheme that involves a pole-placement feedback controller and an optimal proportional–integral–derivative (PID) or fractional-order PID (FOPID) controller is proposed to simultaneously enable the tracking control of the rotary arm and the stabilization of the pendulum arm in an input–output feedback linearized RIP system. The PID controller is optimized first with the particle swarm optimization (PSO) to obtain three optimal gains, and then the other two parameters of the FOPID controller are optimized with the PSO. Compared to the optimized PID controller, the optimized FOPID controller improves the tracking and stabilizing accuracy by 53% and 29%, respectively, and demonstrates better adaptability for tracking different reference signals. Moreover, the hybrid FOPID controller exhibits 74.8% and 53% higher tracking accuracy than previous optimized model reference adaptive control PID (MRAC-PID) and linear–quadratic regulator (LQR) controllers, respectively. The proposed hybrid controllers are also digitized with different rules and sampling times, showing a closer performance between the discrete-time and continuous-time hybrid controllers under smaller sampling times.
A Hybrid Model Reference Adaptive Control System for Multi-Rotor Unmanned Aerial Vehicles
In this paper, a novel model reference adaptive control (MRAC) architecture for nonlinear,
time-varying, hybrid dynamical systems is applied for the first time to design the control system
of a multi-rotor unmanned aerial vehicle (UAV). The proposed control system is specifically
designed to address problems of practical interests involving autonomous UAVs transporting
unknown, unsteady payloads and subject to instantaneous variations both in their state and in
their dynamics. These variations can be due, for instance, to the payload’s dynamics, impacts
between the payload and its casing, and sudden payload dropping and pickup. The proposed
hybrid MRAC architecture improves the UAV’s trajectory tracking performance over classical
MRAC also in the presence of motor failures. The applicability of the proposed framework is
validated numerically through the first use of the high-fidelity simulation environment PyChrono
for autonomous UAV control system testing.
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- Award ID(s):
- 2137159
- PAR ID:
- 10497899
- Editor(s):
- AIAA
- Publisher / Repository:
- American Institute of Aeronautics and Astronautics
- Date Published:
- Journal Name:
- SciTech
- Edition / Version:
- 1
- ISBN:
- 978-1-62410-711-5
- Page Range / eLocation ID:
- 0755
- Subject(s) / Keyword(s):
- Navigation, Control
- Format(s):
- Medium: X Size: 4MB Other: PDF
- Size(s):
- 4MB
- Location:
- Orlando, FL
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.2514/6.2024-0755
