Publications

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In this paper, 1 the equations are formulated to model the dynamic behavior of a wind turbine coupled to the electric grid through a Unified Power Flow Controller (UPFC). This concept is demonstrated in order to treat wind plants more as a controllable energy source rather than a negative load, which is the current trend among renewable energy systems. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device, such as a UPFC, to enable the maximum power output of a wind turbine while meeting the constraints of the bulk electric system. The UPFC is required to operate as both a generator and load (energy storage) on the power system in this design. An illustrative example demonstrates this concept applied to a UPFC with a 1MW fixed speed wind turbine. The wind turbine is operated with multiple wind profiles for below-rated wind power conditions. The wind turbine is connected in series through a UPFC to the infinite bus. Numerical simulation cases are reviewed that best demonstrate the stability and performance of a UPFC as applied to a renewable energy system. © 2012 IEEE.

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In this paper, the swing equations for renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generator system. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device, such as a Unified Power Flow Controller (UPFC), to enable the maximum power output of a wind turbine while meeting the power system constraints on frequency and phase. The UPFC is required to operate as both a generator and load (energy storage) on the power system in this design. Necessary and sufficient conditions for stability of renewable generator systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate. An illustrative example demonstrates this HSSPFC methodology. It includes a 600 kW wind turbine, variable speed variable pitch configuration. The wind turbine is operated with a turbulent wind profile for below-rated wind power conditions. The wind turbine is connected in series through a UPFC to the infinite bus. Numerical simulation cases are reviewed that best demonstrate the stability and performance of HSSPFC as applied to a renewable energy system. © 2011 IEEE.

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The swing equations for renewable generators connected to the grid are developed and a wind turbine is used as an example. The swing equations for the renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generators system. This formulation extends previous results on the analytical verification of the Potential Energy Boundary Surface (PEBS) method to nonlinear control analysis and design and justifies the decomposition of the system into conservative and non-conservative systems to enable a two-step, serial analysis and design procedure. The first step is to analyze the system as a conservative natural Hamiltonian system with no externally applied non-conservative forces. The Hamiltonian surface of the swing equations is related to the Equal-Area Criterion and the PEBS method to formulate the nonlinear transient stability problem. This formulation demonstrates the effectiveness of proportional feedback control to expand the stability region. The second step is to analyze the system as natural Hamiltonian system with externally applied non-conservative forces. The time derivative of the Hamiltonian produces the work/rate (power flow) equations which is used to ensure balanced power flows from the renewable generators to the loads. The Second Law of Thermodynamics is applied to the power flow equations to determine the stability boundaries (limit cycles) of the renewable generators system and enable design of feedback controllers that meet stability requirements while maximizing the power generation and flow to the load. Necessary and sufficient conditions for stability of renewable generators systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate. © 2010 IEEE.

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In this paper, the swing equations for renewable generators are formulated as a natural Hamiltonian system with externally applied non-conservative forces. A two-step process referred to as Hamiltonian Surface Shaping and Power Flow Control (HSSPFC) is used to analyze and design feedback controllers for the renewable generator system. This formulation extends previous results on the analytical verification of the Potential Energy Boundary Surface (PEBS) method to nonlinear control analysis and design and justifies the decomposition of the system into conservative and non-conservative systems to enable a two-step, serial analysis and design procedure. In particular, this approach extends the work done by developing a formulation which applies to a larger set of Hamiltonian Systems that has Nearly Hamiltonian Systems as a subset. The results of this research include the determination of the required performance of a proposed Flexible AC Transmission System (FACTS)/storage device to enable the maximum power output of a wind turbine while meeting the power system constraints on frequency and phase. The FACTS/storage device is required to operate as both a generator and load (energy storage) on the power system in this design. The Second Law of Thermodynamics is applied to the power flow equations to determine the stability boundaries (limit cycles) of the renewable generator system and enable design of feedback controllers that meet stability requirements while maximizing the power generation and flow to the load. Necessary and sufficient conditions for stability of renewable generators systems are determined based on the concepts of Hamiltonian systems, power flow, exergy (the maximum work that can be extracted from an energy flow) rate, and entropy rate.

Active aerodynamic load control of wind turbine blades has been heavily researched for years by the wind energy research community and shows great promise for reducing turbine fatigue damage. One way to benefit from this technology is to choose to utilize a larger rotor on a turbine tower and drive train to realize increased turbine energy capture while keeping the fatigue damage of critical turbine components at the original levels. To assess this rotor-increase potential, Sandia National Laboratories and FlexSys Inc. performed aero/structural simulations of a 1.5MW wind turbine at mean wind speeds spanning the entire operating range. Moment loads at several critical system locations were post-processed and evaluated for fatigue damage accumulation at each mean wind speed. Combining these fatigue damage estimates with a Rayleigh wind-speed distribution yielded estimates of the total fatigue damage accumulation for the turbine. This simulation procedure was performed for both the turbine baseline system and the turbine system incorporating a rotor equipped with FlexSys active aerodynamic load control devices. The simulation results were post-processed to evaluate the decrease in the blade root flap fatigue damage accumulation provided by the active aero technology. The blade length was increased until the blade root flap fatigue damage accumulation values matched those of the baseline rotor. With the new rotor size determined, the additional energy capture potential was calculated. These analyses resulted in an energy capture increase of 11% for a mean wind speed of 6.5m/s.

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This paper presents a new nonlinear control methodology for slewing spacecraft, which provides both necessary and sufficient conditions for stability by identifying the stability boundaries, rigid body modes, and limit cycles. Conservative Hamiltonian system concepts, which are equivalent to static stability of airplanes, are used to find and deal with the static stability boundaries: rigid body modes. The application of exergy and entropy thermodynamic concepts to the work-rate principle provides a natural partitioning through the second law of thermodynamics of power flows into exergy generator, dissipator, and storage for Hamiltonian systems that is employed to find the dynamic stability boundaries: limit cycles. This partitioning process enables the control system designer to directly evaluate and enhance the stability and performance of the system by balancing the power flowing into versus the power dissipated within the system subject to the Hamiltonian surface (power storage). Relationships are developed between exergy, power flow, static and dynamic stability, and Lyapunov analysis. The methodology is demonstrated with two illustrative examples: (1) a nonlinear oscillator with sinusoidal damping and (2) a multi-input-multioutput three-axis slewing spacecraft that employs proportional-integral-derivative tracking control with numerical simulation results.

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This paper develops a novel control system design methodology that uniquely combines: concepts from thermodynamic exergy and entropy; Hamiltonian systems; Lyapunov's direct method and Lyapunov optimal analysis; electric AC power concepts; and power flow analysis. Relationships are derived between exergy/entropy and Lyapunov optimal functions for Hamiltonian systems. The methodology is demonstrated with a couple of fundamental numerical simulation examples: 1) a PID regulator control for a linear mass-spring-damper system and 2) a Duffing oscillator/Coulomb friction nonlinear model that employs PID regulator control. The control system performances are partitioned and evaluated based on exergy generation and exergy dissipation terms. This novel nonlinear control methodology results in both necessary and sufficient conditions for stability of nonlinear systems. © 2006 IEEE.

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Collective systems are typically defined as a group of agents (physical and/or cyber) that work together to produce a collective behavior with a value greater than the sum of the individual parts. This amplification or synergy can be harnessed by solving an inverse problem via an information-flow/communications grid: given a desired macroscopic/collective behavior find the required microscopic/individual behavior of each agent and the required communications grid. The goal of this report is to describe the fundamental nature of the Hamiltonian function in the design of collective systems (solve the inverse problem) and the connections between and values of physical and information exergies intrinsic to collective systems. In particular, physical and information exergies are shown to be equivalent based on thermodynamics and Hamiltonian mechanics.

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.

This report contains the results of a research effort on advanced robot locomotion. The majority of this work focuses on walking robots. Walking robot applications include delivery of special payloads to unique locations that require human locomotion to exo-skeleton human assistance applications. A walking robot could step over obstacles and move through narrow openings that a wheeled or tracked vehicle could not overcome. It could pick up and manipulate objects in ways that a standard robot gripper could not. Most importantly, a walking robot would be able to rapidly perform these tasks through an intuitive user interface that mimics natural human motion. The largest obstacle arises in emulating stability and balance control naturally present in humans but needed for bipedal locomotion in a robot. A tracked robot is bulky and limited, but a wide wheel base assures passive stability. Human bipedal motion is so common that it is taken for granted, but bipedal motion requires active balance and stability control for which the analysis is non-trivial. This report contains an extensive literature study on the state-of-the-art of legged robotics, and it additionally provides the analysis, simulation, and hardware verification of two variants of a proto-type leg design.

This paper 1 develops a novel control system design methodology that uniquely combines: concepts from thermodynamic exergy and entropy; Hamiltonian systems; Lyapunov's direct method and Lyapunov optimal analysis; electric AC power concepts; and power flow analysis. Relationships are derived between exergy/entropy and Lyapunov optimal functions for Hamiltonian systems. The methodology is demonstrated with two fundamental numerical simulation examples: 1) a Duffing oscillator/Coulomb friction nonlinear model that employs PID regulator control and 2) a van der Pol nonlinear oscillator system. The control system performances and/or appropriately identified terms are partitioned and evaluated based on exergy generation and exergy dissipation terms. This novel nonlinear control methodology results in both necessary and sufficient conditions for stability of nonlinear systems.

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The development of lightweight flexible structures that include both advanced control and active material will impact several space application areas. One way to reduce vibration is the combination of advanced control methods such as nonlinear adaptive control plus active structure technology. Active structures with both sensors and actuators, strategically placed along the structure, can suppress vibrations and enhance slewing performance. Active vibration suppression is accomplished with a graphite/epoxy composite structure that includes embedded strain sensors and actuators.