A QP Solver Implementation for Embedded Systems Applied to Control Allocation

Schreppel, Christina; Brembeck, Jonathan

doi:10.3390/computation8040088

Cited by 4 publications

(1 citation statement)

References 12 publications

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“…Developing efficient algorithms for solving quadratic optimization problems is crucial for implementing allocation control systems. Schreppel and Brembeck (2020) introduce a quadratic programming solver designed specifically for embedded platforms. The solver has been demonstrated to be effective in control allocation for over-actuated vehicles, offering improved computational efficiency compared to existing methods.…”

Section: Introductionmentioning

confidence: 99%

Vertical take-off and hover to cruise transition for a hybrid UAV using model predictive controller and MPC allocation

Mohammadi,

Tayefi,

Zhu

2023

AEAT

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Purpose Dual-thrust hybrid unmanned aerial vehicle (UAV) technology offers a highly robust and efficient system that incorporates the take-off and landing capabilities of rotary-wing aircraft with the endurance capacities of fixed-wing aircraft. The purpose of this study is to model and control a hybrid UAV in three distinct flight modes: rotary-wing, fixed-wing and over-actuated model. Design/methodology/approach Model predictive control (MPC) along with linear models are applied to design controllers for the rotary-wing or vertical take-off and transition to the fixed-wing flight. The MPC algorithm is implemented with two approaches, first in its usual form and then in a new form with the help of tracking error variables as state variables. Findings Because the tracking error variables are more compatible with the cost function used in MPC, the results improve significantly. This is especially important for a safe and stable transition from rotary-wing to fixed-wing flight, which should be done quickly. The authors also propose a control allocation strategy with MPC algorithm to exploit the thrust and control inputs of both rotary-wing and fixed-wing systems for the transition phase. As the control system is over-actuated, the proposed algorithm distributes the control signal among the actuators better than the MPC alone. The numerical results show that the flight trajectory is also improved. Originality/value The research background is reviewed in the introduction section. The other sections are originally developed in this paper to the best of the authors’ knowledge.

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Section: Introductionmentioning

confidence: 99%