Optimal Multi-Channel Output Feedback Control to Damp Power System Oscillations using Battery Energy Storage.
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An investigation is made of the problem of predicting the attitude of satellites under the influence of external disturbing torques. The attitude dynamics are first expressed in a perturbation formulation which is then solved by the multiple scales approach. The independent variable, time, is extended into new scales, fast, slow, etc., and the integration is carried out separately in the new variables. The theory is applied to two different satellite configurations, rigid body and dual spin, each of which may have an asymmetric mass distribution. The disturbing torques considered are gravity gradient and geomagnetic. Finally, as multiple time scales approach separates slow and fast behaviors of satellite attitude motion, this property is used for the design of an attitude control device. A nutation damping control loop, using the geomagnetic torque for an earth pointing dual spin satellite, is designed in terms of the slow equation.
A helicopter in-flight simulation was conducted to determine the effects of variations in roll damping, roll sensitivity, and pitch and roll rate cross-coupling on helicopter flying qualities in a low altitude maneuver. The experiment utilized the UH-1H helicopter in-flight simulator, which is equipped with the V/STOLAND avionics system. The response envelope of this vehicle allowed simulation of configurations with low to moderate damping and sensitivity. A visual, low level slalom course was set up, consisting of constant speed and constant altitude S-turns around the 1000 ft makers of an 8000 ft runway. Results are shown in terms of Cooper-Harper pilot ratings, pilot commentary, and statistical and frequency analyses of the lateral characteristics. These results show good consistency with previous ground simulator results and are compared with existing flying qualities criteria.
The stability of active contour models or 'snakes' is studied. It is shown that the modification of snake parameters using adaptive systems improves both the stability of the snakes and the boundaries obtained. The adaptive snakes perform better with images of varying contrasts, noisy images and images with different curvatures along the boundaries. The computational costs at each iteration for the adaptive snakes is still of order N, where N is the number of points on the snakes. Comparisons of the results for non-adaptive and adaptive snakes are shown using both computer simulations and satellite images.
To meet the flight control damping requirement, baffles of various configurations have been devised to increase the natural viscous damping and decrease the magnitude of the slosh forces and torques. In the design of slosh baffles, the most widely used damping equation is the one derived by Miles, which is based on the experiments of Keulegan and Carpenter. This equation has been used in predicting damping of the baffled tanks in different diameters ranging from 12 to 112 inches. The analytical expression of Miles equation is easy to use, especially in the design of complex baffle system. Previous investigations revealed that some experiments had shown good agreements with the prediction method of Miles, whereas other experiments have shown significant deviations. For example, damping from Miles equation differs from experimental measurements by as much as 100 percent over a range of tank diameters from 12 to 112 inches, oscillation amplitudes from 0.1 to 1.5 baffle widths, and baffle depths of 0.3 to 0.5 tank radius. Previously, much of this difference has been attributed to experimental scatter. A systematical study is needed to understand the damping physics of baffled tanks, to identify the difference between Miles equation and experimental measurement, and to develop new semi-empirical relations to better represent the real damping physics. The approach of this study is to use CFD technology to shed light on the damping mechanisms of a baffled tank. First, a 1-D Navier-Stokes equation representing different length scales and time scales in the baffle damping physics is developed and analyzed. A well validated CFD solver, developed at NASA MSFC, Loci-STREAM-VOF, is applied to study vorticity field around the baffle and around the fluid interface to highlight the dissipation mechanisms at different slosh amplitudes. Previous measurement data are then used to validate the CFD damping results. The study found several critical parameters controlling fluid damping from a baffle: local slosh amplitude to baffle thickness (A/t), surface liquid depth to tank radius (h/R), local slosh amplitude to baffle width (A/W); and non-dimensional slosh frequency. The simulation highlights three significant damping regimes where different mechanisms dominate. The study proves that the previously found discrepancies between Miles equation and experimental measurement are not due to the measurement scatter, but rather due to different damping mechanisms at various slosh amplitudes. The limitations on the use of Miles equation are discussed based on the flow regime.
The objective of this paper is to conduct experiments in fuel optimal propulsive maneuvers of flexible spacecraft in order to verify and extend recently developed theory and apply it to various classes of spacecraft. Topics covered in viewgraph format include: impulse damping control by experimental verification; impulse damping of the SCOLE reflector and mast; fuel optimal control of rotating flexible beam; fuel optimal aerobrake maneuvers.
The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.
This paper describes recent advances in structural quieting technology as applied to active truss structures intended for high precision space based optics applications. Collocated active damping control loops are designed in order to impedance match piezoelectric active members to the structure. Noncollocated control loops are also studied in relation to controlling lightly damped structures.
The process is described of analysis, design, digital implementation, and subsonic testing of an active control flutter suppression system for a full span, free-to-roll wind tunnel model of an advanced fighter concept. The design technique uses a frequency domain representation of the plant and used optimization techniques to generate a robust multi input/multi output controller. During testing in a fixed-in-roll configuration, simultaneous suppression of both symmetric and antisymmetric flutter was successfully shown. For a free-to-roll configuration, symmetric flutter was suppressed to the limit of the tunnel test envelope. During aggressive rolling maneuvers above the open-loop flutter boundary, simultaneous flutter suppression and maneuver load control were demonstrated. Finally, the flutter damping controller was reoptimized overnight during the test using combined experimental and analytical frequency domain data, resulting in improved stability robustness.
Appropriate damping control of the inter-area oscillation would ensure the grid stability and maintain the tie-line power transfer capability. In this paper, we proposed a novel reinforcement learning (RL) based power oscillation damping (POD) controller that uses Thyristor Controlled Series Compensators (TCSC) to damp inter-area oscillations. By leveraging the unbiased gradient direction estimation of the natural evolution strategy (NES), we successfully regulated the power flows on the tie-lines and damped inter-area oscillations through dynamically modulating the inserted reactance of the TCSC. The proposed RL-based POD controller has been tested on both two-area four-machine system and North American Minni-WECC system. Extensive studies have demonstrated the excellent performance of the proposed RL-based TCSC POD controller in damping inter-area oscillations.
Grid-forming control is widely envisioned as core technology ensuring stable operation of future power systems with increasing deployment of converter-interfaced renewable generation. However, research on grid forming control of wind turbines, especially under faults, is still in its early stages. In this context, this paper augments dual-port grid-forming control for type IV wind turbines with auxiliary controls to enable reliable fault ride through capabilities. In particular, the proposed control does not require a dc chopper or mode switching to grid-following control. Instead, energy-balancing dual-port GFM control is augmented with active rotor speed damping control and threshold virtual impedance for current limiting during faults. Different operating conditions of wind turbines are considered in a detailed electromagnetic transient simulation study to validate the effectiveness of the proposed control.
A series of flight maneuvers were developed to cover the range of flight conditions and to define the repeatability and hysteresis of the sensors. Initial flights were made with two sensors at the + or - 68 percent span and 60 percent and 70 percent chord stations. The primary effort in simulation program development was to modify the LRC General Aviation Simulator (GAS) Fortran programs to allow execution on the MSU UNIVAC 1106. A simple model of the sensor-servo stall deterrent system was developed. A one degree of freedom model of pitch dynamics of the airplane and stall deterrent system was developed to make initial estimates of the control system gains. A position error plus rate damping control algorithm was found to have acceptable characteristics.
Graph theoretic techniques are used to study controllability of linear systems which represent large flexible orbiting space systems with inherent damping. The controllability of the pair of matrices representing the system state and control influence matrices is assured when all states in the model are reachable in a digraph sense from at least one input and also when the term rank of a Boolean matrix whose non trivial components are based on the state and control influence matrices has a term rank of the order of the state vector. The damping matrix does not influence the required number of actuators but gives flexibility to the possibility locations of the actuators for which the system is controllable.
Control power and damping requirements for visual hovering tasks in vtol aircraft-bell x-14 testing
Excessive vibration of turbomachinery blades causes high cycle fatigue (HCF) problems requiring damping treatments to mitigate vibration levels. Based on the technical challenges and requirements learned from previous turbomachinery blade research, a feasibility study of resonant damping control using shunted piezoelectric patches with passive and active control techniques has been conducted on cantilever beam specimens. Test results for the passive damping circuit show that the optimum resistive shunt circuit reduces the third bending resonant vibration by almost 50%, and the optimum inductive circuit reduces the vibration by 90%. In a separate test, active control reduced vibration by approximately 98%.
This paper presents experimental and computational comparisons of three active damping control laws applied to a complex laboratory structure. Two reduced structural models were used with one model being corrected on the basis of measured mode shapes and frequencies. Three control laws were investigated, a time-invariant linear quadratic regulator with state estimation and two direct rate feedback control laws. Experimental results for all designs were obtained with digital implementation. It was found that model correction improved the agreement between analytical and experimental results. The best agreement was obtained with the simplest direct rate feedback control.
This paper proposes a reinforcement learning-based method to maximize power generation for a direct-drive marine hydrokinetic turbine. A high levelized cost of energy (LCOE) is preventative in the widespread adoption of many marine energy conversion technologies. A straightforward way to reduce LCOE is to increase conversion efficiency and ensure maximum energy generation. The proposed method utilizes a damping control methodology, varying applied generator torque via a linear relationship between the applied damping coefficient and rotor speed. A state-action-reward-state-action (SARSA) algorithm has been used to learn the optimal control action for a given flow velocity. The proposed SARSA methodology uses Gaussian radial basis functions to create a three-dimensional surface to estimate the relationship between damping coefficient, incoming flow velocity, and coefficient of power (C p ). Here, the SARSA algorithm was compared against a baseline optimal tip speed ratio controller over a year-long flow velocity case profile while considering the effects of biofouling on the turbine system, where the proposed RL method generated 0.92% more energy than the baseline.
The concept of a large-stroke adaptive stiffness cable-device for damping control of space structures with large mass is introduced. The cable is used to provide damping in several examples, and its performance is shown through numerical simulation results. Displacement and velocity information of how the structure moves is used to determine when to modify the cable's stiffness in order to provide a damping force.