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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Report presents improved algorithms for controlling kinematically redundant robotic manipulators, producing unique configuration for each end-effector location. Furthermore, they generally produce configurations in which no interference between robot boom and payload or base structures. Report presents comparison between various other robot-kinematic algorithms.
An application of the new optimization algorithm Static/Dynamic Control (SDC) to the design of low-thrust interplanetary trajectories is presented. The interplanetary trajectory is integrated with a multi-body force model and may include gravity assists.
A preliminary design of the Cassini Thrust Vector Control algorithm which controls the spacecraft attitude during main engine burns is described. The discussion includes software architecture, sensor/actuator characteristics, and vehicle dynamics, as well as controller design and margin analysis via clasical methods, and performance evaluation via simulation.
It is suggested that nearly any control algorithm that can be used for fixed-based manipulators also can be employed in the control of free-floating space manipulator systems, with the additional conditions of estimating or measuring a spacecraft's orientation and of avoiding dynamic singularities. This result is based on the structural similarities between the kinematic and dynamic equations for the same manipulator but with a fixed base. Barycenters are used to formulate the kinematic and dynamic equations of free-floating space manipulators. A control algorithm for a space manipulator system is designed to demonstrate the value of the analysis.
A G-RAC attitude-control algorithm is used to minimize maneuver execution error in a spacecraft with a flexible appendage when said spacecraft must induce translational momentum by firing (in open loop) large thrusters along a desired direction for a given period of time. The controller is dynamic with two integrators and requires measurement of only the angular position and velocity of the spacecraft. The global stability of the closed-loop system is guaranteed without having access to the states describing the dynamics of the appendage and with severe saturation in the available torque. Spacecraft apply open-loop thruster firings to induce a desired translational momentum with an extended appendage. This control algorithm will assist this maneuver by stabilizing the attitude dynamics around a desired orientation, and consequently minimize the maneuver execution errors.
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.
New digital control algorithms have been developed to achieve the desired transmissibility function for a microgravity isolation system. Two approaches have been presented for the controller design in the context of a single degree of freedom system for which an attractive electromagnet is used as the actuator. The relative displacement and the absolute acceleration of the mass have been used as feedback signals. The results from numerical studies are presented. It has been found that the resulting transmissibility is quite close to the desired function. Also, the maximum coil currents required by new algorithms are smaller than the maximum current demanded by the previously proposed lead/lag method.
The purpose of this informal paper is to discuss certain robustness issues associated with existing adaptive control algorithms. A modeling framework for incorporating high-frequency unknown dynamics in the adaptive control framework is suggested. Possible fundamental limitations of existing adaptive control framework is suggested. Possible fundamental limitations of existing adaptive control algorithms are also discussed, with emphasis upon their closed-loop stability properties in the presence of unmodeled high-frequency dynamics.
New digital control algorithms were developed to achieve the desired acceleration transmissibility function. The attractive electromagnets have been taken as actuators. The relative displacement and the acceleration of the mass were used as feedback signals. Two approaches were developed to find that controller transfer function in Z-domain, which yields the desired transmissibility at each frequency. In the first approach, the controller transfer function is obtained by assuming that the desired transmissibility is known in Z-domain. Since the desired transmissibility H sub d(S) = 1/(tauS+1)(exp 2) is given in S-domain, the first task is to obtain the desired transmissibility in Z-domain. There are three methods to perform this task: bilinear transformation, and backward and forward rectangular rules. The bilinear transformation and backward rectangular rule lead to improper controller transfer functions, which are physically not realizable. The forward rectangular rule does lead to a physically realizable controller. However, this controller is found to be marginally stable because of a pole at Z=1. In order to eliminate this pole, a hybrid control structure is proposed. Here the control input is composed of two parts: analog and digital. The analog input simply represents the velocity (or the integral of acceleration) feedback; and the digital controller which uses only relative displacement signal, is then obtained to achieve the desired closed-loop transfer function. The stability analysis indicates that the controller transfer function is stable for typical values of sampling period. In the second approach, the aforementioned hybrid control structure is again used. First, an analog controller transfer function corresponding to relative displacement feedback is obtained to achieve the transmissibility as 1/(tauS+1)(exp 2). Then the transfer function for the digital control input is obtained by discretizing this analog controller transfer function via bilinear transformation. The stability of the resulting Z-domain closed loop system is analyzed. Also, the frequency response of the Z-domain closed-loop transfer function is determined to evaluate the performance of the control system.
ABSTRACT This paper focuses on the development of cyber‐resilient gradient‐based optimisation algorithms and theoretical proof for grid‐interactive distributed energy resource (DER) control to enable two grid services of virtual power plants (VPPs) dispatch and grid voltage regulation, considering the communication and security impacts. Firstly, the combined DER dispatch and voltage regulation as a real‐time gradient‐based optimisation problem is recapped. Thereafter, we consider a probabilistic traffic model to characterise packet delays and loss in a communication network, and study how the delays enter the process of information exchange among the grid measurement units, local DER controllers and the grid control centre that execute this control algorithm in a coordinated manner. Then, a strategy combining delay thresholds and message update rules is proposed to immunity the asynchrony resulting from the communications traffic and it avoids possible numerical instabilities and sensitivities of the power tracking and voltage regulation capabilities, resulting as cyber‐resilient DER control algorithms. Additionally, their convergence is theoretically proved. Effectiveness of proposed cyber‐resilient algorithms has been validated on the IEEE 37‐bus system in terms of convergence, VPP tracking and voltage regulation performance for smart distribution systems with high penetration of DERs.
This report summarizes the activities on "Implementation of Real-Time Feedback Flow Control Algorithms on a Canonical Testbed." The work summarized consists primarily of two parts. The first part summarizes our previous work and the extensions to adaptive ID and control algorithms. The second part concentrates on the validation of adaptive algorithms by applying them to a vibration beam test bed. Extensions to flow control problems are discussed.
This paper examines the robustness properties of existing adaptive control algorithms to unmodeled plant high-frequency dynamics and unmeasurable output disturbances. It is demonstrated that there exist two infinite-gain operators in the nonlinear dynamic system which determines the time-evolution of output and parameter errors. The pragmatic implications of the existence of such infinite-gain operators is that: (1) sinusoidal reference inputs at specific frequencies and/or (2) sinusoidal output disturbances at any frequency (including dc), can cause the loop gain to increase without bound, thereby exciting the unmodeled high-frequency dynamics, and yielding an unstable control system. Hence, it is concluded that existing adaptive control algorithms as they are presented in the literature referenced in this paper, cannot be used with confidence in practical designs where the plant contains unmodeled dynamics because instability is likely to result. Further understanding is required to ascertain how the currently implemented adaptive systems differ from the theoretical systems studied here and how further theoretical development can improve the robustness of adaptive controllers.
The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.
This paper presents convergence analysis of a novel data-driven feedback control algorithm designed for generating online controls based on partial noisy observational data. The algorithm comprises a particle filter-enabled state estimation component, estimating the controlled system’s state via indirect observations, alongside an efficient stochastic maximum principle-type optimal control solver. By integrating weak convergence techniques for the particle filter with convergence analysis for the stochastic maximum principle control solver, we derive a weak convergence result for the optimization procedure in search of optimal data-driven feedback control. Numerical experiments are performed to validate the theoretical findings.
This technical note provides a mathematical proof of Corollary 1 from the paper 'A Nonlinear Model Predictive Control Algorithm with Proven Robustness and Resolvability' that appeared in the 2006 Proceedings of the American Control Conference. The proof was omitted for brevity in the publication. The paper was based on algorithms developed for the FY2005 R&TD (Research and Technology Development) project for Small-body Guidance, Navigation, and Control [2].The framework established by the Corollary is for a robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems that guarantees the resolvability of the associated nite-horizon optimal control problem in a receding-horizon implementation. Additional details of the framework are available in the publication.
This paper presents a field deployment experiment of a real-time traffic signal control algorithm. We implemented the Model Predictive Control (MPC) algorithm based on Virtual Phase-Link (VPL) model. We selected the deployment locations and times based on an energy saving potential concept. We developed a set of experiment systems to enable the deployment including sensing, processing, and actuating components. We tested the systems rigorously before the experiment days. We reported the key procedures on the experiment days including the steps took, real-time control procedure, and the monitoring of the experiment. We evaluated the impact of the deployment with the changes in delay and energy consumption.
Precision Formation Flying is an enabling technology for a variety of proposed space-based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), the associated MAXIM pathfinder mission, and the Stellar Imager. An essential element of the technology is the control algorithm. This paper discusses the development of a nonlinear, six-degree of freedom (6DOF) control algorithm for maintaining the relative position and attitude of a spacecraft within a formation. The translation dynamics are based on the equations of motion for the restricted three body problem. The control law guarantees the tracking error convergences to zero, based on a Lyapunov analysis. The simulation, modelled after the MAXIM Pathfinder mission, maintains the relative position and attitude of a Follower spacecraft with respect to a Leader spacecraft, stationed near the L2 libration point in the Sun-Earth system.
A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.