In this paper, we consider a distributed control approach for blade pitch control of a wind farm which consists of several floating offshore wind turbines. Each wind turbine is modeled as a discrete-time linear model based on the aerodynamics simulator for wind turbines called FAST (Fatigue, Aerodynamics, Structures, and Turbulence). We formulate an optimization problem with an objective function of a quadratic form to coordinate a total power generation determined by a Transmission System Operator (TSO) while keeping fluctuation of the generator speed and oscillation of each wind turbine sufficiently small. The numerical example with the FAST simulator shows the effectiveness of the proposed distributed control method.

RC radar is often used as a preliminary survey in renewal works for reinforced concrete (RC) structures. Because the RC radar linearly scans linear polarization antennas, the linear targets such as reinforcing bars and thin power lines perpendicular to the polarization is sometimes missed and is damaged in works of concrete coring. Therefore, a freehand RC radar is required which can flexibly scan to the arbitrary direction with arbitrary rotation angle. In this paper, we propose a calibration method of alignment and sensitivity errors of sensors for 2D positioning system of antennas using two optical mouse sensors. In addition, we integrate RC radar and positioning system, and show that freehand scan of circularly polarized antenna is effective for visualization of buried thin electric wire with 3D imaging results.

In this paper, we consider a new approach to data-driven controller tuning for time-delay systems. The Smith compensator is widely known as an effective method for time-delay systems. In the case where a mathematical model of a time-delay system is completely known, it is well known that the desired response can be completely achieved by using suitable feedback controller using the mathematical model. In this paper, we address the case where a mathematical model is unknown and it is difficult to execute an ideal experiment for identification. A direct usage of the data is one of the rational approaches in such a case. Here, we apply Virtual Internal Model Tuning (VIMT), which was a data-driven controller update method by using output data and was proposed by the authors, to the Smith compensator. We explain how VIMT is expand to this class of the controllers. We also consider the meaning of the cost function used in the proposed method. Finally, we illustrate an experimental example to show the validity and the effectiveness of the proposed method.

This paper proposes a D-scaling technique with stochastic scaling elements whose randomness is relevant to stochastic systems with dynamics determined by an i.i.d. stochastic process. The scaling effect is verified with a numerical example.