Rush D. Robinett

Nonlinear Aeroelastic Power Flow Control for Wind Turbines

This paper applies a novel nonlinear power flow control technique to a nonlinear stall flutter problem. A nonlinear aerodynamic and structural model is developed that is representative of the first torsional mode of a nominal 1.5 MW rated power wind turbine blade. This model is analyzed using the power flow control technique to determine the limit cycle behavior of the nonlinear stall flutter condition of the first torsional mode. Also, this model is further analyzed to determine the eectiveness of the feedback control on nonlinear flutter suppression as well as demonstrating that the limit cycle defines a stability boundary. Further indepth discussion will be included for the final paper. In addition, the specific wind conditions for a 1.5MW wind turbine will be identified and the relationship and important connection to this analysis shown. The closer the wind turbine can safely operate to dynamic stall, the greater the energy that can be generated.

3. Introduction to Dynamic Programming

This book concerns the use of a method known as dynamic programming (DP) to solve large classes of optimization problems. We will focus on discrete optimization problems for which a set or sequence of decisions must be made to optimize (minimize or maximize) some function of the decisions. There are of course numerous methods to solve discrete optimization problems, many of which are collectively known as mathematical programming methods. Our objective here is not to compare these other mathematical programming methods with dynamic programming. Each has advantages and disadvantages, as discussed in many other places. However, we will note that the most prominent of these other methods is linear programming. As its name suggests, it has limitations associated with its linearity assumptions whereas many problems are nonlinear. Nevertheless, linear programming and its variants and extensions (some that allow nonlinearities) have been used to solve many real world problems, in part because very early in its development software tools (based on the simplex method) were made available to solve linear programming problems. On the other hand, no such tools have been available for the much more general method of dynamic programming, largely due to its very generality. One of the objectives of this book is to describe a software tool for solving dynamic programming problems that is general, practical, and easy to use, certainly relative to any of the other tools that have appeared from time to time. One reason that simplex-based tools for solving linear programming problems have been successful is that, by the nature of linear programming, problem specification is relatively easy. A basic LP problem can be specified essentially as a system or matrix of equations with a finite set of numerical variables as unknowns. That is, the input to an LP software tool can be provided in a tabular form, known as a tableaux. This also makes it easy to formulate LP problems as a spreadsheet. This led to spreadsheet system providers to include in their product an LP solver, as is the case with Excel. A software tool for solving dynamic programming problems is much more difficult to design, in part because the problem specification task in itself

Design tools for complex dynamic security systems.

The development of tools for complex dynamic security systems is not a straight forward engineering task but, rather, a scientific task where discovery of new scientific principles and math is necessary. For years, scientists have observed complex behavior but have had difficulty understanding it. Prominent examples include: insect colony organization, the stock market, molecular interactions, fractals, and emergent behavior. Engineering such systems will be an even greater challenge. This report explores four tools for engineered complex dynamic security systems: Partially Observable Markov Decision Process, Percolation Theory, Graph Theory, and Exergy/Entropy Theory. Additionally, enabling hardware technology for next generation security systems are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.

Modeling, system identification, and control for slosh-free motion of an open container of liquid

This report discusses work performed under a Cooperative Research And Development Agreement (CRADA) with Corning, Inc., to analyze and test various techniques for controlling the motion of a high speed robotic arm carrying an open container of viscous liquid, in this case, molten glass. A computer model was generated to estimate the modes of oscillation of the liquid based on the shape of the container and the viscosity of the liquid. This fluid model was experimentally verified and tuned based on experimental data from a capacitive sensor on the side of the container. A model of the robot dynamics was also developed and verified through experimental tests on a Fanuc S-800 robot arm. These two models were used to estimate the overall modes of oscillation of an open container of liquid being carried by a robot arm. Using the estimated modes, inverse dynamic control techniques were used to determine a motion profile which would eliminate waves on the liquid`s surface. Experimental tests showed that residual surface waves in an open container of water at the end of motion were reduced by over 95% and that in-motion surface waves were reduced by over 75%.