This paper presents a new technique to identify the system parameters without using the system governing equations. This technique is the time series prediction using neural network. The theoretical model was applied using simulations, after that the experiments were done to get the suitable construction for the neural model. A comparison between neural network and placket's model is discussed. The advantages and disadvantages of both models were explained. The main idea of neural network is based on back-propagation algorithm. The equations and steps for iteration are presented and the relation between changing the number of iteration with the system frequency. The controller used is pole placement controller based on the neural network results as a system model.

Kites can be used to harvest wind energy at higher altitudes while using only a fraction of the material required for conventional wind turbines. In this work, we present the kite system of Kyushu University and demonstrate how experimental data can be used to train machine learning regression models. The system is designed for 7 kW traction power and comprises an inflatable wing with suspended kite control unit that is either tethered to a fixed ground anchor or to a towing vehicle to produce a controlled relative flow environment. A measurement unit was attached to the kite for data acquisition. To predict the generated tether force, we collected input–output samples from a set of well-designed experimental runs to act as our labeled training data in a supervised machine learning setting. We then identified a set of key input parameters which were found to be consistent with our sensitivity analysis using Pearson input–output correlation metrics. Finally, we designed and tested the accuracy of a neural network, among other multivariate regression models. The quality metrics of our models show great promise in accurately predicting the tether force for new input/feature combinations and potentially guide new designs for optimal power generation.

Abstract. In wind energy research, airborne wind energy systems are one of the promising energy sources in the near future. They can extract more energy from high altitude wind currents compared to conventional wind turbines. This can be achieved with the aid of aerodynamic lift generated by a wing tethered to the ground. Significant savings in investment costs and overall system mass would be obtained since no tower is required. To solve the problems of wind speed uncertainty and kite deflections throughout the flight, system identification is required. Consequently, the kite governing equations can be accurately described. In this work, a simple model was presented for a tether with a fixed length and compared to another model for parameter estimation. In addition, for the purpose of stabilizing the system, fuzzy control was also applied. The design of the controller was based on the concept of Mamdani. Due to its robustness, fuzzy control can cover a wider range of different wind conditions compared to the classical controller. Finally, system identification was compared to the simple model at various wind speeds, which helps to tune the fuzzy control parameters.

No abstract

Modelling, system identification and the controller for variable length quad-rotors are presented in this paper. Modelling was derived using Newton-Euler method, then small disturbance theory was used for linearization. Plackett's algorithm was used for system identification to predict the system parameters. Mass-varying problem is the main objective of this paper, and the effect of changing the system parameters was discussed in detail. The system parameters are updated in real-time during flight with low sample time. The PID-Accelerator controller of the quad-rotor was updated also in real-time based on the change of the system identification output. The attitude and altitude control of the quad-rotor were presented using an adaptive classical controller. Now the tethered mass-varying quad-rotor can be simulated. The objective of this work is to make the quad rotors fly for long time and to be robust for variable inputs comes from the tether. The simulation results of the system identification and control responses of the attitude and altitude are presented in this paper. The disturbance of the wind was also considered in the controller design.

Kites can be used to harvest wind energy with substantially lower material and environmental footprints and a higher capacity factor than conventional wind turbines. In this paper, we present measurement data from seven individual tow tests with the kite system developed by Kyushu University. This system was designed for 7 kW traction power and comprises an inflatable wing of 6 m2 surface area with a suspended kite control unit that is towed on a relatively short tether of 0.4 m by a truck driving at constant speed along a straight runway. To produce a controlled relative flow environment, the experiment was conducted only when the background wind speed was negligible. We recorded the time-series of 11 different sensor values acquired on the kite, the control unit and the truck. The measured data can be used to assess the effects of the towing speed, the flight mode and the lengths of the control lines on the tether force.

No abstract

No abstract