This paper presents the design and simulation results of a model predictive controller (MPC) applied to the longitudinal dynamics of a lighter-than-air wind energy system being pioneered by Altaeros Energies. The unique Altaeros design features a traditional horizontal axis wind turbine that is held aloft by a buoyant shroud, which is tethered to a ground based platform. This structure provides access to strong, high-altitude winds, requires minimal setup, and builds upon proven aerostat components, making the system an attractive component in expanding wind energy throughout the world. However, because the system replaces a conventional tower with tethers, its dynamics are highly susceptible to variations in the wind. In particular, the control system must keep the shroud pitch angle and tether tensions within acceptable bounds in order to maintain stable operation and remain within structural limitations of the system. In this paper, we apply MPC to achieve desirable longitudinal system performance while simultaneously enforcing the constraints. We describe the longitudinal dynamic model of the system, detail the linear MPC design, and provide simulation results on both the linearized and nonlinear system for a variety of real-world wind conditions, including a Dryden turbulence model and data acquired from the Altaeros functional prototype test site at Loring Air Force Base in Limestone, Maine.
- Dynamic Systems and Control Division
Model Predictive Longitudinal Control of a Lighter-Than-Air Wind Energy System Available to Purchase
Weng, R, Balasubramanian, K, Vermillion, C, & Kolmanovsky, I. "Model Predictive Longitudinal Control of a Lighter-Than-Air Wind Energy System." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 2: Legged Locomotion; Mechatronic Systems; Mechatronics; Mechatronics for Aquatic Environments; MEMS Control; Model Predictive Control; Modeling and Model-Based Control of Advanced IC Engines; Modeling and Simulation; Multi-Agent and Cooperative Systems; Musculoskeletal Dynamic Systems; Nano Systems; Nonlinear Systems; Nonlinear Systems and Control; Optimal Control; Pattern Recognition and Intelligent Systems; Power and Renewable Energy Systems; Powertrain Systems. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 275-284. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8613
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