九州大学学術情報リポジトリ
Kyushu University Institutional Repository
カイト風力発電システムの飛行経路の適応制御
タレク, ナエム, モハメッド, ディーフ
https://doi.org/10.15017/1866340
出版情報：Kyushu University, 2017, 博士（学術）, 課程博士 バージョン：
権利関係：
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ltifil Jt $ : Adaptive Flight· Path Control of Kite Power System (j] -1 r M:36fflV 7. 'T AO)flH'rW:/1,0)~/litl{ffll) Title
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ltifilJtpsJ$0)~\§' Thesis Summary
In this thesis, the system identification was used to get a more accurate description for the steering dynamics of the kite in rea~time; the characteristics of the kite are varying with time because the Vling is inflatable and flexible. Also, the Vlind speed can1 be measured in rea~time so it is impossible to obtain the lift and drag forces during flight This technique especially is used to identify the system parameters as it can calculate them Vlithout iteration (one cirectional calculation) which means no time loses, also any initial conditions are valid even if they are zeros Vlithout getting any singularity in the solver. Regarding the real flight test, the system is fully defined using the system identification in rea~time, so the controller gains don't need to be fixed during the whole flight test. In particular, the folloVling research work has been undertaken:
1 . Ttie proper implementation for the kite model which defines the kite motion with suitable assumptions.
2 . Simulate the mathematical model in Maflab/Simulink to get real-time solver for the non-linear model.
3. Derive and implement.two system identification algorithms to predict the kite governing equations.
4 . Validate the results got from the system identification algorithms Vlith the mathematical model of the kite.
5 . Design adaptive and fuzzy control to stabilize the kite, then compare the results Vlith classical control in different Vlind conditions.
6 . Validate the_ system identification results Vlith real flight test achieved in TU Delft for the variabie length tether system.
7 . Design an adaptive controller for the Vlinch to calculate the force generated from the variable length kite system.
The novelty of this work is to use an algorithm that is valid for any kite size and any tether length. So it can overcome the uncertainty of the kite modeling. This algorithm needs the steering values from the motors and the course angle from the sensors. Thus, .no additional information is needed such as the Vlind speed or the mathematical model of the kite to identify the system that shall be controlled.
This thesis is divided into six main chapters. Chapter 1 is the introduction which gives a complete virm of the background of the 1.1 Vlind energy and the 1.3 kite power system.
Chapter 2 gives a full description of the kite model inclucing the 2.2 kinematics framework, after that the Vlind speed estimation was discussed in detail to get a mathematical model for the Vlind speed at the 2.3 kite altitude.
The Flight Path Planner (FPP) was explained to show the kite trajectory during flight and to show the parameters affect the 2.4 kite trajectory. Moreover, the Flight Path Controller (FPC) was derived to stabilize the kite using 2.5 PID controller. The simulation of the model was implemented using MaHab/Simulink.
In chapter 3, two system identification algorithms were applied to identify the system parameters in real-time. The full algorithms are discussed in detail to show the matching between the system model given in 2 and the (3.3, · 3.2) system identification algorithms.
In chapter4, two controllers are applied to stabilize the kite; the first controller js the 4.2 adaptive controller and it was designed based on the parameters result from the 3.2 system identification algorithm. The other controller is the 4.3 fuzzy controller, and it was used based on the experience we got from the system identification algorithms given in section 3.3. For each section of the two main sections, the simulation resul1s were presented to compare between them and the 2.5 classical control.
Chapter 5 is divided into two main sections; the first section 5.1 discusses the experimental resul1s got from TU Delft for variable length tether system. Then, these resul1s were discussed to identify the parameters of the kite in real-time. The parameters resulting .from this section were analyzed using the system identification algorithm in chapter 3. The 5.2 other section presen1s simulation resul1s for the force generated from the winch due to the change in the tether length.
In chapter 6, a complete design for the Quad-Rotor is presented from scratch as a benchmark problem to test the system identification algorithms and the controller. The chapter is divided into four main sections. The first section introduces the previous work achieved as shown in section 6.1. The mathematical model of the Quad-Rotor is presented in detail 6.2 to derive a SISO model that would be used for the control design. The third section discusses the 6.3 neural network; it was used as a system identification algorithm. The last section discusses the 6.4 control design, it gives a detailed analysis of the control design process supported by simulation and experimental resul1s.
