Power Wing Airfoil Flight Control for Carousel Energy Systems

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Solution Overview

Problem

Current systems lack the ability to automatically control the flight of power wing airfoils in a predictive manner, particularly for 'carousel' type systems, which are prone to local maxima, oscillations, and driving instabilities due to inadequate modeling and control methodologies.

Innovation Solution

A system and process for automatically controlling the flight of power wing airfoils using onboard detecting means such as accelerometers and magnetometers, combined with ground-based sensors, to process real-time data and adjust the flight trajectory for maximum lift and kinetic energy extraction, employing robust control theories and predictive strategies to anticipate future flight conditions and mitigate errors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional control methodologies are used for power wing airfoils, then device complexity is reduced, but reliability deteriorates due to inability to handle multi-variable non-linear systems with robustness requirements

Engineering Contradiction:
Improvecontrol system robustnessVSAvoidcontrol system complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent implements a robust identification methodology that continuously monitors system behavior and updates control parameters based on measured deviations from expected performance. This feedback mechanism allows the control system to adapt to parametric variations and unmodeled dynamics, thereby improving reliability without requiring excessive complexity in the base control architecture.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The control system dynamically adjusts parameters based on real-time system identification results. By changing control parameters adaptively rather than using fixed complex algorithms, the system achieves robustness against parametric variations while maintaining manageable device complexity.

Inventive Principle:
Principle #35Parameter changes

2Reliability

If approximate mathematical models are used for control design, then device complexity is reduced, but reliability deteriorates due to uncertainty in modeling multi-variable non-linear systems

Engineering Contradiction:
Improvecontrol accuracyVSAvoidmodel identification complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent performs system identification and model calibration during a preliminary phase before normal operation. By characterizing the system dynamics in advance and storing identification results for use during normal control operations, the system achieves accurate control without requiring complex real-time modeling, thus improving reliability while limiting identification complexity to the calibration phase.

Inventive Principle:
Principle #10Preliminary action

3Productivity

If predictive control strategies are implemented, then productivity is improved through maximum energy extraction, but device complexity increases due to need for future state prediction and error mitigation

Engineering Contradiction:
Improveenergy production efficiencyVSAvoidpredictive control complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The predictive control strategy uses pre-computed optimal trajectories and prediction models that are prepared in advance. By having prediction algorithms and optimal control sequences ready beforehand, the system can efficiently extract maximum energy without requiring excessively complex real-time predictive computations, thus improving productivity while managing device complexity.

Inventive Principle:
Principle #10Preliminary action

4Reliability

If robust identification methods are used for system characterization, then reliability is improved through accurate model representation, but device complexity increases due to multiple identification techniques required

Engineering Contradiction:
Improvemodel accuracyVSAvoididentification system complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The robust identification process is divided into distinct segments or phases, each focusing on specific system characteristics. By segmenting the identification task into manageable portions (e.g., linear parameter identification, non-linear characteristic characterization, validation phases), the system achieves comprehensive and accurate modeling without requiring all identification techniques to operate simultaneously, thus improving reliability while controlling device complexity.

Inventive Principle:
Principle #1Segmentation

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The solution enables efficient and stable flight control, maximizing energy production by avoiding local maxima and oscillations, ensuring real-time adaptation to changing wind conditions and improving the overall operational stability of power wing airfoils in 'carousel' systems.

Implementation Method 1

first detecting means (3) on board the power wing airfoil (2) adapted to detect first pieces of information (3a) dealing with at least position and orientation in space of the airfoil (2) itself and three-axes accelerations to which it is subjected

Methodology Applied
Scientific EffectAccelerometer: Accelerometer

Implementation Method 2

first detecting means (3) on board the power wing airfoil (2) adapted to detect first pieces of information (3a) dealing with at least position and orientation in space of the airfoil (2) itself

Methodology Applied
Scientific EffectMagnetometer: Magnetometer

Implementation Method 3

driving unit (9) equipped with alternately motored winches (9a) to which the airfoil (2) itself is connected through two respective driving cables (21)

Methodology Applied
Scientific EffectWinch mechanism: Differential Windlass

Implementation Method 4

system for converting the kinetic energy of Aeolian currents into electric energy through the predictive and adaptative control of the flight of power wing airfoils connected to a system of the 'carousel' type

Methodology Applied
Scientific EffectWind power: Wind Power

Data Source

PatentEP2016284B1A device for the production of electric energy and process for the automatic control of said device
Publication Date: 2012.08.15 KITE GEN RES SRL
  • EP2016284B1 patent drawingFigure 1~2a
  • EP2016284B1 patent drawingFigure 2b~3
  • EP2016284B1 patent drawingFigure 4a~4b

AI summary

A system (1) is described for automatically controlling the flight of at least one power wing airfoil (2) , comprising first detecting means (3) on board of such power wing airfoil (2) adapted to detect first pieces of information (3a) dealing with at least one position and one orientation in space of the power wing airfoil (2) and accelerations to which the power wing airfoil (2) is subjected; second detecting means (5) on the ground adapted to detect tension on the driving cables (21) of the power wing airfoil (2) and a position of a driving unit (9) counterweight; processing and controlling means (7) adapted to transform the contents of such information (3a, 5a) into a mechanical drive operating on the winches of the driving unit (9) to drive the power wing airfoil (2) along a flight trajectory TVl, TV2 , TV3, ..., TVn maximising a "lift" effect generated on the power wing airfoil (2) . A process is further described for automatically controlling the flight of at least one power wing airfoil (2) through the system (1) .