Aykut Özgün Önol

Model Predictive Control for Energy Maximization of Small Vertical Axis Wind Turbines

In this paper, a model predictive control (MPC) approach is presented to maximize the energy generated by a small vertical axis wind turbine (VAWT) subject to current and voltage constraints of electrical and power electronic components. Our method manipulates a load coefficient and optimizes the control trajectory over a prediction horizon such that a cost function that measures the deviation from the maximum available energy and the violation of current and voltage constraints is minimized. Simplified models for the VAWT and a permanent magnet generator have been used. A number of simulations have been carried out to demonstrate the performance of the proposed method at step and oscillatory wind conditions. Furthermore, impacts of the constraints on energy generation have been investigated. Moreover, the performance of the MPC has been compared with a typical maximum power point tracking algorithm in order to show that maximizing the instantaneous power does not mean maximizing the energy; and simulation results have shown that the MPC outperforms the maximum power point tracking algorithm in terms of generated energy by allowing deviations from the maximum power instantaneously for future gains in energy generation.Copyright

Hardware-in-the-loop simulations and control design for a small vertical axis wind turbine

Control design plays an important role in wind energy conversion systems in achieving high efficiency and performance. In this study, hardware-in-the-loop (HIL) simulations are carried out to design a maximum power point tracking (MPPT) algorithm for small vertical axis wind turbines (VAWTs). Wind torque is calculated and applied to an electrical motor that drives the generator in the HIL simulator, which mimics the dynamics of the rotor. To deal with disturbance torques in the HIL system, a virtual plant is introduced to obtain an error between the speeds in the HIL system and virtual plant. This error is used by a proportional-integral (PI) controller to generate a disturbance torque compensation signal. The MPPT algorithm is tested in the HIL simulator under various wind conditions, and the results are compared with numerical simulations. The HIL simulator successfully mimics the dynamics of the VAWT under various wind conditions and provides a realistic framework for control designs.

Towards Autonomous Grasping with Robotic Prosthetic Hands

For an effective use of a robotic prosthetic, smooth transition between the states of this human-in-the-loop cyber-physical system (or autonomous operation) is crucial. In order to achieve that, taking into account the uncertainties in the robotic system may be as significant as anticipating the human intent. In this study, we present two risk measures associated with a simple grasping task based on the pre-grasp position and orientation of the robotic hand, and analyze them by using a model of a dexterous mechatronic prosthetic arm to simulate a simple grasping task. Moreover, we develop a hybrid position and force grasp controller and use a grasp quality metric to assess the grasps. 34 simulations with different pre-grasp poses were performed to investigate the relationship between the grasp quality and the risk measures as well as the sensitivity of the grasp quality to the pre-grasp position of the hand. Results show that the proposed risk metrics and the pre-grasp position correlate with the grasp quality, yet they are not sufficient to predict the outcome.

Comparisons of controller performance for small-scale vertical axis wind turbines

Small-scale vertical axis wind turbines (VAWTs) are attractive for portable power generation. Controller performance is very important in rapidly varying gusty winds commonly observed in urban and rural areas. In this paper, a hill-climb searching (HSC) maximum power point tracking (MPPT), an energy-maximizing model predictive control (MPC) and a simple nonlinear control (SNC) as an MPC surrogate are presented. The control algorithms are tested through a software-only electromechanical model and with hardware-in-the-loop test-bed that includes electromechanical and power electronics components. Effects of power coefficient oscillations on dynamic performance are investigated. Results show that proposed controllers perform satisfactorily for wind gust and real wind profiles; the SNC serves as a viable surrogate for the MPC; the model-free, wind speed sensorless MPPT is favorable for small-scale applications; and power coefficient oscillations do not have a significant impact on the dynamic performance of the controllers.

Modeling, hardware-in-the-loop simulations and control design for small-scale vertical axis wind turbines

In this study, we present a methodology for the assessment of overall performance for vertical axis wind turbines (VAWT) with straight blades. Salient features of our approach include a validated computational fluid dynamics (CFD) model and a hardware-in-the loop (HIL) test-bed. The two-dimensional, time-dependent CFD model uses the k-e turbulence model and is coupled with the dynamics of the rotor involving friction and generator torques. The power coefficient curve for the rotor is obtained from the CFD simulations by varying the generator torque over time, and then used in the HIL test-bed that consists of an electrical motor, a gearbox, a permanent magnet synchronous generator, and an electronic load. In this setup, the VAWT rotor is mimicked by the electrical motor based on a power coefficient curve obtained from CFD simula-tions. Effects of the electrical conversion and control design on the overall performance of the VAWT are studied in the HIL setup. Additionally, a simple nonlinear control (SNC) algorithm that mimics a model predictive controller and two different adaptations of the maximum power point tracking (MPPT) algorithm with fixed and variable step-sizes are designed and implemented in HIL simulations. According to results, the generator has a profound effect on the overall power output and the efficiency of the turbine; and the SNC and MPPT algorithms perform satisfactorily under step wind conditions.