Parameterized Trajectory Optimization and Tracking Control of High Altitude Parafoil Generation

Xinyu Long, Mingwei Sun, Minnan Piao and Zengqiang Chen
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Xinyu Long: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Mingwei Sun: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Minnan Piao: College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Zengqiang Chen: College of Artificial Intelligence, Nankai University, Tianjin 300350, China

Energies, 2021, vol. 14, issue 22, 1-20

Abstract: Parafoil trajectory directly affects the power generation of a high-altitude wind power generation (HAWPG) device. Therefore, it is particularly important to optimize the parafoil trajectory and then to track it effectively. In this paper, the trajectory of the parafoil at high altitudes is optimized and tracked in a comprehensively parameterized manner. Both the complex dynamic characteristics of the parafoil and the dexterous demand of the high-altitude controller are considered. Firstly, the trajectory variables and control signals are parameterized as Lagrange polynomials in terms of the corresponding values at the selected nodes. Then, the Radau pseudospectral method (PSM) is employed to reformulate the original dynamic trajectory optimization problem into a static nonlinear programming (NLP) problem. By doing so, the parameterized optimal trajectory, which has the maximum net power generation, can be obtained. To attenuate the strong nonlinear, multivariable and coupling characteristics of the flexible parafoil, a bandwidth parameterized linear extended state observer (ESO) is used to estimate and reject these dynamics explicitly in a unified way. Finally, the simulation results demonstrate the effectiveness of the proposed parameterized trajectory optimization and control strategies. The main contribution of this study is that complicated nonlinear parafoil dynamics with a complex trajectory can be well regulated by a PID-type linear time-invariant controller, which is appealing for practitioners.

Keywords: pseudospectral method (PSM); trajectory optimization; nonlinear programming (NLP); extended state observer (ESO) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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