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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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At least 253 records · Page 14

Introduction to Advanced Engine Control Concepts

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. The Controls and Dynamics Branch at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. The key enabling technologies for an Intelligent Propulsion System are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance operational reliability and component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This presentation describes the current activities of the Controls and Dynamics Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Sanjay, Garg↗

Reversible control over the distribution of chemical inhomogeneities in multiferroic BiFeO3

Abstract Despite the appeal of flawless order, semiconductor technology has demonstrated that implanting inhomogeneities into single-crystalline materials is pivotal for modern electronics. However, the influence of the local arrangement of chemical inhomogeneities on the material’s functionalities is underexplored. In this work, we control the distribution of chemical inhomogeneities in La 3+ -substituted ferroelectric BiFeO 3 thin films. By means of a stress- and composition-driven phase transition, we trigger the formation of a lattice of La 3+ -rich and La 3+ -poor layers. This ordering correlates with the emergence of an antipolar phase. An electric field restores the original ferroelectric phase and re-randomizes the distribution of the La 3+ inhomogeneities. Leveraging these insights, we tune the polar/antipolar phase coexistence to set the net polarization of La 0.15 Bi 0.85 FeO 3 to any desired value between its saturation limits. Finally, we control the net polarization response in device-compliant capacitor heterostructures to show that inhomogeneity-distribution control is a valuable tool in the design of functional oxide electronics.

Science & Technology - Other Topics↗

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗

Adaptive Multi-Agent Systems for Constrained Optimization

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Macready, William↗

Distributed traffic signal control using fuzzy logic

We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections.

Chiu, Stephen↗

On adaptive regulation of flexible spacecraft

It is pointed out that the regulation of shape and attitude disturbances in large space structures (LSS) using adaptive control remains an actively studied, yet controversial approach, just as adapative control itself. The controversy arises because the utility of many methods of adapatively controlling distributed parameter systems (DPS) is unsubstantiated. However, it appears that adaptive control can be applied to solve problems in LSS control which are not amenable to more common control methods. The present investigation has the objective to clarify the application of adaptive control to LSS. Attention is given to the characteristics of adaptive model control, aspects of simultaneous mode shape adaption, questions of multivariable simultaneous identification and control, and direct adaptive multivariable control.

Lawrence, D. A.↗

Eigenstructure assignment for a thrust-vectored high angle-of-attack aircraft

Eigenstructure assignment is utilized to design flight control laws for a thrust-vectored aircraft at several different angles of attack. An interesting characteristic of the aircraft model is that the control distribution matrix is rank-deficient. Also, the effectiveness of the control inputs varies with the angle of attack. A pseudocontrol strategy is used to reduce the control space to two dimensions. After the eigenstructure assignment design is complete, the controller is mapped back to the original five-dimensional control space. The designs are shown to exhibit acceptable multivariable stability margins at the aircraft inputs.

Sobel, Kenneth M.↗

Discrete control of linear distributed systems with application to the deformable primary mirror of a large orbiting telescope

The results are presented of a detailed study of the discrete control of linear distributed systems with specific application to the design of a practical controller for a plant representative of a telescope primary mirror for an orbiting astronomical observatory. The problem of controlling the distributed plant is treated by employing modal techniques to represent variations in the optical figure. Distortion of the mirror surface, which arises primarily from thermal gradients, is countered by actuators working against a backing structure to apply a corrective force distribution to the controlled surface. Each displacement actuator is in series with a spring attached to the mirror by means of a pad intentionally introduced to restrict the excitation of high-order modes. Control is exerted over a finite number of the most significant modes.

Creedon, J. F.↗

Holographic signal processing for control of a flexible beam

A robust control system is presented for damping vibrations in a cantilevered beam. The distributed deflections of the beam are sensed using real-time holography. A hybrid processor which uses optical and digital processors is proposed to implement a distributed control algorithm. The controller is designed using the linear-quadratic-Gaussian method to add damping to a finite number of vibrational modes.

Barsky, Michael F.↗

A feedback linearization approach to spacecraft control using momentum exchange devices

Recent developments in the area of nonlinear control theory have shown how coordiante changes in the state and input spaces can be used with nonlinear feedback to transform certain nonlinear ordinary differential equations into equivalent linear equations. These feedback linearization techniques are applied to resolve two problems arising in the control of spacecraft equipped with control moment gyroscopes (CMGs). The first application involves the computation of rate commands for the gimbals that rotate the individual gyroscopes to produce commanded torques on the spacecraft. The second application is to the long-term management of stored momentum in the system of control moment gyroscopes using environmental torques acting on the vehicle. An approach to distributing control effort among a group of redundant actuators is described that uses feedback linearization techniques to parameterize sets of controls which influence a specified subsystem in a desired way. The approach is adapted for use in spacecraft control with double-gimballed gyroscopes to produce an algorithm that avoids problematic gimbal configurations by approximating sets of gimbal rates that drive CMG rotors into desirable configurations. The momentum management problem is stated as a trajectory optimization problem with a nonlinear dynamical constraint. Feedback linearization and collocation are used to transform this problem into an unconstrainted nonlinear program. The approach to trajectory optimization is fast and robust. A number of examples are presented showing applications to the proposed NASA space station.

Dzielski, John Edward↗

Fleet Assignment Using Collective Intelligence

Product distribution theory is a new collective intelligence-based framework for analyzing and controlling distributed systems. Its usefulness in distributed stochastic optimization is illustrated here through an airline fleet assignment problem. This problem involves the allocation of aircraft to a set of flights legs in order to meet passenger demand, while satisfying a variety of linear and non-linear constraints. Over the course of the day, the routing of each aircraft is determined in order to minimize the number of required flights for a given fleet. The associated flow continuity and aircraft count constraints have led researchers to focus on obtaining quasi-optimal solutions, especially at larger scales. In this paper, the authors propose the application of this new stochastic optimization algorithm to a non-linear objective cold start fleet assignment problem. Results show that the optimizer can successfully solve such highly-constrained problems (130 variables, 184 constraints).

Antoine, Nicolas E.↗

Interactive robot control system and method of use

A robotic system includes a robot having joints, actuators, and sensors, and a distributed controller. The controller includes command-level controller, embedded joint-level controllers each controlling a respective joint, and a joint coordination-level controller coordinating motion of the joints. A central data library (CDL) centralizes all control and feedback data, and a user interface displays a status of each joint, actuator, and sensor using the CDL. A parameterized action sequence has a hierarchy of linked events, and allows the control data to be modified in real time. A method of controlling the robot includes transmitting control data through the various levels of the controller, routing all control and feedback data to the CDL, and displaying status and operation of the robot using the CDL. The parameterized action sequences are generated for execution by the robot, and a hierarchy of linked events is created within the sequence.

Sanders, Adam M.↗

Robustness of a distributed neural network controller for locomotion in a hexapod robot

A distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.

Chiel, Hillel J.↗

Product Distribution Theory for Control of Multi-Agent Systems

Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS's). First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint stare of the agents. Accordingly we can consider a team game in which the shared utility is a performance measure of the behavior of the MAS. For such a scenario the game is at equilibrium - the Lagrangian is optimized - when the joint distribution of the agents optimizes the system's expected performance. One common way to find that equilibrium is to have each agent run a reinforcement learning algorithm. Here we investigate the alternative of exploiting PD theory to run gradient descent on the Lagrangian. We present computer experiments validating some of the predictions of PD theory for how best to do that gradient descent. We also demonstrate how PD theory can improve performance even when we are not allowed to rerun the MAS from different initial conditions, a requirement implicit in some previous work.

Lee, Chia Fan↗

A procedure for optimal control of flexible surface vibrations

The vibration controller design for a thin flexible surface with a given boundary is formulated as an unconstrained optimization problem. It is shown that this formulation is equivalent to a system of uncoupled optimization problems each of which is a linear regulator design problem for a second-order modal system. The regulator solutions give the gains on the modal amplitude and velocity associated with each modal system. For the constrained control case corresponding to a finite number of actuators, an approximation to the optimal distributed control is given. For the case of a limited number of physical sensors, a dual approach yields a system of second-order observers or filters. Simulations indicate that the constrained controller has a satisfactory performance as long as the number of actuators is more than half the number of controlled modes.

Caglayan, A. K.↗

Eigenstructure assignment for the control of highly augmented aircraft

Eigenstructure assignment is utilized to design flight control laws for aircraft with many control effectors. It is shown that a previous eigenstructure design for the flight propulsion control coupling (FPCC) aircraft lateral dynamics with three control surfaces exhibits a lack of stability robustness because the control distribution matrix is nearly rank-deficient. A method is mapped back, reducing the control space to two dimensions by using the singular value decomposition. After the design is complete, the controller is mapped back to the original three-dimensional control space. This design approach yields a controller with both smaller gains and improved multivariable stability margins at the aircraft inputs. An interesting characteristics of the control mapping, as applied to the given example, is that the most effective inputs have the larger gains while the less effective inputs have smaller gains.

Sobel, Kenneth M.↗

Data-Driven Mean-Corrected Recursive Estimation-Based Optimal DER Dispatch for Distribution System Voltage Control

Recent advances in smart inverters offer opportunities to mitigate adverse grid impacts caused by high penetrations of distributed photovoltaics (PV) in distribution grids, such as voltage violations. Here, this paper proposes a novel measurement-driven optimal power flow (OPF)-based distributed energy resource management system (DERMS) voltage regulation via recursive sensitivity estimation informed coordinated control of distributed PV inverters. The proposed approach leverages available grid and controllable DER measurements, eliminating reliance on system model information while being adaptive and robust to volatile operating conditions. A mean-corrected recursive ridge regression (MCRRR) algorithm is proposed for sensitivity estimation, continuously refining the sensitivity model through a closed-form solution. It effectively manages varying grid operating conditions, such as changes in power injections and topology reconfiguration, to facilitate a time-varying update of the Load Sensitivity Factors (LSF). The proposed approach is formulated as a linear programming (LP) problem and is thus scalable to larger-scale distribution systems. Its effectiveness and efficiency are demonstrated on a realistic distribution feeder with high PV penetrations in Southern California, USA.

14 SOLAR ENERGY↗

Finite-dimensional discrete-time control of linear distributed parameter systems

Systems described by partial differential equations have an infinite-dimensional state space. Feedback control of such distributed parameter systems must be accomplished by finite-dimensional controllers to be implemented by on-line digital computers. A further practical constraint is that the controller must operate in discrete (rather than continuous) time. This paper investigates the stability of such distributed parameter feedback controllers in closed-loop with the actual system.

Balas, M. J.↗