Shalom D. Ruben

A Model-Free Approach to Wind Farm Control Using Game Theoretic Methods

This brief explores the applicability of recent results in game theory and cooperative control to the problem of optimizing energy production in wind farms. One such result is a model-free control strategy that is completely decentralized and leads to efficient system behavior in virtually any distributed system. We demonstrate that this learning rule can provably maximize energy production in wind farms without explicitly modeling the aerodynamic interaction amongst the turbines.

Surveying Game Theoretic Approaches for Wind Farm Optimization

This paper surveys recent results in game theory and cooperative control and highlights their implications for the problem of optimizing energy production in wind farms. One such result is a simple payoff-based learning rule that is completely decentralized and leads to an efficient configuration of actions in virtually any distributed system. We demonstrate that this learning rule can be used to provably maximize energy production in wind farms without explicitly modeling the aerodynamic interaction amongst the turbines.

A data-driven model for wind plant power optimization by yaw control

This paper presents a novel parametric model that will be used to optimize the yaw settings of wind turbines in a wind plant for improved electrical energy production of the whole wind plant. The model predicts the effective steady-state flow velocities at each turbine, as well as the resulting electrical energy productions, as a function of the axial induction and the yaw angle of the different rotors. The model has a limited number of parameters that are estimated based on data. Moreover, it is shown how this model can be used to optimize the yaw settings using a game-theoretic approach. In a case study we demonstrate that our novel parametric model fits the data generated by a high-fidelity computational fluid dynamics model of a small wind plant, and that the data-driven yaw optimization control has great potential to increase the wind plants electrical energy production.

Real-time optimal commutation for minimizing thermally induced inaccuracy in multi-motor driven stages

In this paper minimum power commutation laws of permanent-magnet synchronous linear motors are extended to multiple-motor driven systems. A system-wide view of commutation is shown to exploit the redundancy of motor coils and motor force generation that exist in over actuated motion platforms. We propose a novel commutation law, that is only realizable by a multiple-motor system view, which minimizes total power subject to the constraint that the thermal distortion at the motion platform work space, caused by the motor coil heating, is minimized. Due to the added constraint, there is no closed-form solution and the problem is shown to be non-convex. This problem solution is proven to be equally solved by the combination of an algebraic and convex problem. To realize the commutation laws, a custom embedded solver, using an interior-point method, is described to solve the convex problem in real-time and is shown to converge to a solution, in under 35 @ms, within the update rate of our system running at over 9 KHz.

Open-path dual-comb spectroscopy to an airborne retroreflector

We demonstrate a new technique for spatial mapping of multiple atmospheric gas species. This system is based on high-precision dual-comb spectroscopy to a retroreflector mounted on a flying multi-copter. We measure the atmospheric absorption over long open-air paths to the multi-copter with comb-tooth resolution over 1.57 to 1.66 pm, covering absorption bands of CO2, Cm, H2O and isotopologues. When combined with GPS-based path length measurements, a fit of the absorption spectra retrieves the dry mixing ratios versus position. Under well-mixed atmospheric conditions, retrievals from both horizontal and vertical paths show stable mixing ratios as expected. This approach can support future boundary layer studies as well as plume detection and source location.

Mechatronics and Control of a Precision Motion Stage for Nano-Manufacturing

High precision motion is critical in the semiconductor industry and as feature size continues to decrease, the need for higher precision increases. This paper presents the control system design and integration of a novel multi-degree of freedom precision stage for nano-manufacturing. It is composed of a 6 DOF wafer holder and a 3 DOF module holder. The modules can be chosen for a desired task, such as a nano-imprint lithography module. Capacitance gauges, interferometers, and photo detectors provide position feedback of the stage. Piezo-electric actuators and linear motors, that produce two orthogonal forces each, produce the desired output. Modeling of the coordinate transformation among the spaces of sensors, stage position, and actuators along with dynamic modeling of the stage is presented. Controller design, hardware, and software is described and results comparing simulation and implementation show a closed-loop positioning of less than 1 nm error in x and y and 0.01 arc seconds in θ z with a sensor noise level of less than 0.2 nm.Copyright

Optimal commutation laws by real-time optimization for multiple motor driven systems

This paper addresses commutation laws of brushless motor coils for multiple-degree-of-freedom motion. By exploiting the redundancy of motor coils and motor force generation that exist in over actuated motion platforms, we propose a commutation law, which generates the required forces while minimizing the effect of motor coil heat generation on thermal distortion on the motion platform work space. To realize the commutation laws in real-time, a real-time iterative solution, using an interior-point method, is described and shown to solve this problem in under 35 microseconds, within the update rate of our system running at over 9KHz.

Respect the implementation: Using NI myRIO in undergraduate control education

In this paper we present, due to its low-cost, portability, and high-functionality, the National Instruments (NI) myRIO as an excellent platform for hands-on in systems and control education, from advanced to beginner courses. That said, implementing control algorithms by the beginner, especially, is not to be taken lightly on digital platforms like the myRIO. We show, using a simple electric circuit as a plant, how a student can get some catastrophic results when implementing even a simple proportional controller. These catastrophic results stem partially from discretization choice, determinism of the sampling rate, and sampling rate limitations. Throughout the paper we discuss how to enhance determinism and prevent catastrophic results by being aware of your hardwares limitations.