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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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After a short recall concerning the aeroelastic equations, active control law based on optimal stochastic control theory is synthesized for a wing flutter and gust response. Robustness of the control system due to structured and unstructured uncertainties is considered. Robustness recovery technique is applied to improve the stability margin.
A problem in SCOLE is that of slewing an offset antenna on a long flexible beam-like truss attached to the space shuttle, with rather stringent pointing accuracy requirements. The relevant methodology aspects in robust feedback-control design for stability augmentation of the beam using on-board sensors is examined. It is framed as a stochastic control problem, boundary control of a distributed parameter system described by partial differential equations. While the framework is mathematical, the emphasis is still on an engineering solution. An abstract mathematical formulation is developed as a nonlinear wave equation in a Hilbert space. That the system is controllable is shown and a feedback control law that is robust in the sense that it does not require quantitative knowledge of system parameters is developed. The stochastic control problem that arises in instrumenting this law using appropriate sensors is treated. Using an engineering first approximation which is valid for small damping, formulas for optimal choice of the control gain are developed.
The problem of computing open-loop, fuel- and time-optimal control inputs for flexible space structures in the face of modeling uncertainty is investigated. Robustified, fuel- and time-optimal pulse sequences are obtained by solving a constrained optimization problem subject to robustness constraints. It is shown that 'bang-off-bang' pulse sequences with a finite number of switchings provide a practical tradeoff among the maneuvering time, fuel consumption, and performance robustness of uncertain flexible space structures.
The Air Transportation Technology Program at Princeton University is a program that emphasizes graduate and undergraduate student research. The program proceeded along six avenues during the past year: microburst hazards to aircraft, intelligent failure tolerant control, computer-aided heuristics for piloted flight, stochastic robustness of flight control systems, neural networks for flight control, and computer-aided control system design.
As one of the near-term goals of the President's Vision for Space Exploration, establishment of a multi-person lunar base will require high-endurance power systems which are independent of the sun, and can operate without replenishment for several years. These requirements may be obtained using nuclear power systems specifically designed for use on the lunar surface. While it is envisioned that such a system will generally be supervised by humans, some of the evolutions required maybe semi or fully autonomous. The entire base complement for near-term missions may be less than 10 individuals, most or all of which may not be qualified nuclear plant operators and may be off-base for extended periods thus, the need for power system autonomous operation. Startup, shutdown, and load following operations will require the application of advanced control and health management strategies with an emphasis on robust, supervisory, coordinated control of, for example, the nuclear heat source, energy conversion plant (e.g., Brayton Energy Conversion units), and power management system. Autonomous operation implies that, in addition to being capable of automatic response to disturbance input or load changes, the system is also capable of assessing the status of the integrated plant, determining the risk associated with the possible actions, and making a decision as to the action that optimizes system performance while minimizing risk to the mission. Adapting the control to deviations from design conditions and degradation due to component failures will be essential to ensure base inhabitant safety and mission success. Intelligent decisions will have to be made to choose the right set of sensors to provide the data needed to do condition monitoring and fault detection and isolation because of liftoff weight and space limitations, it will not be possible to have an extensive set of instruments as used for earth-based systems. Advanced instrumentation and control technologies will be needed to enable this critical functionality of autonomous operation. It will be imperative to consider instrumentation and control requirements in parallel to system configuration development so as to identify control-related, as well as integrated system-related, problem areas early to avoid potentially expensive work-arounds . This paper presents an overview of the enabling technologies necessary for the development of reliable, autonomous lunar base nuclear power systems with an emphasis on system architectures and off-the-shelf algorithms rather than hardware. Autonomy needs are presented in the context of a hypothetical lunar base nuclear power system. The scenarios and applications presented are hypothetical in nature, based on information from open-literature sources, and only intended to provoke thought and provide motivation for the use of autonomous, intelligent control and diagnostics.
This article focuses on the speed planning problem for connected and automated vehicles (CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalized intersections on the road is considered. The eco-driving problem is formulated as a data-driven chance-constrained robust optimization problem. Effective red-light duration (ERD) is defined as a random variable, and describes the feasible passing time through the signalized intersections. Usually, the true probability distribution for ERD is unknown. Consequently, a data-driven approach is adopted to formulate chance constraints based on empirical sample data. This incorporates robustness into the eco-driving control problem with respect to uncertain signal timing. Dynamic programming (DP) is employed to solve the optimization problem. The simulation results demonstrate that the proposed method can generate optimal speed reference trajectories with 40% less vehicle fuel consumption, while maintaining the arrival time at a similar level compared to a modified intelligent driver model (IDM). The proposed control approach significantly improves the controller's robustness in the face of uncertain signal timing, without requiring to know the distribution of the random variable a priori.
The flexibility and robustness of a monitor and control (M&C) system are a direct result of the underlying interprocessor communications architecture. A new architecture for M&C at the Deep Space Communications Complexes (DSCC's) has been developed based on the Manufacturing Message Specification (MMS) process control standard of the Open System Interconnection (OSI) suite of protocols. This architecture has been tested both in a laboratory environment and under operational conditions at the Deep Space Network (DSN) experimental Venus station (DSS-13). The Venus experience in the application of OSI standards to support M&C has been extremely successful. MMS meets the functional needs of the station and provides a level of flexibility and responsiveness previously unknown in that environment. The architecture is robust enough to meet current operational needs and flexible enough to provide a migration path for new subsystems. This paper will describe the architecture of the Venus M&C system, discuss how MMS was used and the requirements this imposed on other parts of the system, and provide results from systems and operational testing at the Venus site.
Dynamic-inversion-based flight control laws present an attractive alternative to conventional gain-scheduled designs for high angle-of-attack maneuvering, where nonlinearities dominate the dynamics. Dynamic inversion is easily applied to the aircraft dynamics requiring a knowledge of the nonlinear equations of motion alone, rather than an extensive set of linearizations. However, the robustness properties of the dynamic inversion are questionable especially when considering the uncertainties involved with the aerodynamic database during post-stall flight. This paper presents a simple analysis and some preliminary results of simulations with a perturbed database. It is shown that incorporating integrators into the control loops helps to improve the performance in the presence of these perturbations.
To ensure high quality TSIS science measurements, stringent requirements were levied on the pointing system performance. Several factors complicated the design of the pointing system controller including uncertainty in knowledge of the ISS base motion jitter, the use of direct drive brushless DC motors for the gimbal system, and the presence of TSIS structure low frequency modes. This paper will describe the modeling, simulation, analysis, and robust design techniques employed to reduce risk resulting in a pointing system that met requirements on-orbit.
Distribution systems with high penetration of uncertain solar generation call for advanced control strategies of photovoltaics (PVs) inverters. This paper proposes a data-driven distributionally robust optimization (DDDRO) approach to optimally controlling the PV inverters to improve the system operation performance under solar power uncertainties. In the proposed DDDRO approach, a Wasserstein ball-based method is proposed to construct the distributional ambiguity set to model the uncertainties of PV generation through partial observations of historical data without knowing exact probability distributions. We further reformulate the computationally intractable DDDRO model to a mixed integer second order cone programming (MISOCP) problem. The effectiveness and out-of-sample performance of the proposed approach have been demonstrated on a modified IEEE 33-node system. We conduct a comparative study to compare the proposed method with traditional chance constrained programming (CCP). It shows that the proposed DDDRO approach can provide a less conservative yet robust solution to minimize the worse-case expectation of the total network loss while maintaining nodal voltages in a secure range.
In order for microreactors to be economically competitive, operation costs will need to be minimized through some degree of autonomous control. Previous work has demonstrated the effectiveness of reinforcement learning (RL) for load-following control in a drum-controlled microreactor. This study extends that work by exploring the potential of RL to independently control each of the reactor’s drums. We compare a single-agent RL approach with a multi-agent RL (MARL) framework, testing them for generalization across different load-following power profiles and control timescales, and for robustness in cases of randomly disabled control drums. Since the point kinetics simulation environment used in this study cannot resolve spatial effects, we assume that in the absence of spatially localized disturbances, optimal drum movements should be symmetrical. We demonstrate that single-agent RL is able to achieve accurate performance only when symmetric actions are ignored; otherwise, it fails to train a useful controller. Meanwhile, the MARL framework performs symmetric actions by design and trains a robust, accurate agent, as evidenced by mean absolute errors in power matching of 0.41% for the training power profile, 0.68% for a profile with half the drums disabled, and 0.21% for a profile on a realistic load-following time horizon.
The flexibility and robustness of a monitor and control (M&C) system are a direct result of the underlying inter-processor communications architecture. A new architecture for M&C at the Deep Space Communications Complexes (DSCCs) has been developed based on the Manufacturing Message Specification (MMS) process control standard of the Open System Interconnection (OSI) suite of protocols. This architecture has been tested both in a laboratory environment and under operational conditions at the Deep Space Network (DSN) experimental Venus station (DSS-13). The Venus experience in the application of OSI standards to support M&C has been extremely successful. MMS meets the functional needs of the station and provides a level of flexibility and responsiveness previously unknown in that environment...
This paper reviews and extends the fractional representation theory. In particular, new and powerful robustness results are presented. This new theory is utilized to develop a preliminary design methodology for finite dimensional control of a class of linear evolution equations on a Banach space. The design is for stability in an input-output sense, but particular attention is paid to internal stability as well.
Despite the recent development of several scalable, robust, and resilient control approaches with superior convergence properties considering an increasing penetration of distributed energy resources (DERs), cognitive oversights often simplify several aspects of the cyber–physical power system in the controller development. Here, following the identification of the limitations of classical controller definitions, we justify alternative definitions of voltage control approaches classifiers considering three inter-disciplinary domains: (i) power system, (ii) optimization and decision-making, and (iii) networking and cyber-security, to develop a taxonomy for helping in real-world comparative performance analysis and deployability of these controllers. We observe that classical and introduced domain-based definitions together can better classify the control algorithms.
This paper presents a numerical investigation of an active structural acoustic control strategy for coupled aircraft-style bays. While structural coupling can destabilize or limit the performance of some model-based decentralized control systems, fullycoupled centralized control strategies are impractical for typical aircraft containing several hundred bays. An alternative is to use classical rate feedback with matched, collocated transducer pairs to achieve active damping. Unfortunately, due to the conservative nature of this strategy, stability is guaranteed at the expense of achievable noise reduction. Therefore, this paper describes the development of a combined control strategy using robust active damping in addition to a high-authority controller based on linear quadratic Gaussian (LQG) theory. The combined control system is evaluated on a tensioned, two-bay model using piezoceramic actuators and ideal point velocity sensors. Transducer placement on the two-bay structure is discussed, and the advantages of a combined control strategy are presented.
This paper describes a combined control strategy designed to reduce sound radiation from stiffened aircraft-style panels. The control architecture uses robust active damping in addition to high-authority linear quadratic Gaussian (LQG) control. Active damping is achieved using direct velocity feedback with triangularly shaped anisotropic actuators and point velocity sensors. While active damping is simple and robust, stability is guaranteed at the expense of performance. Therefore the approach is often referred to as low-authority control. In contrast, LQG control strategies can achieve substantial reductions in sound radiation. Unfortunately, the unmodeled interaction between neighboring control units can destabilize decentralized control systems. Numerical simulations show that combining active damping and decentralized LQG control can be beneficial. In particular, augmenting the in-bandwidth damping supplements the performance of the LQG control strategy and reduces the destabilizing interaction between neighboring control units.
This paper presents flight test results of a robust linear baseline controller with and without composite adaptive control augmentation. The flight testing was conducted using the NASA Generic Transport Model as part of the Airborne Subscale Transport Aircraft Research system at NASA Langley Research Center.
The concept of damage-mitigating control is to minimize fatigue (as well as creep and corrosion) damage of critical components of mechanical structures while simultaneously maximizing the system dynamic performance. Given a dynamic model of the plant and the specifications for performance and stability robustness, the task is to synthesize a control law that would meet the system requirements and, at the same time, satisfy the constraints that are imposed by the material and structural properties of the critical components. The authors present the concept of damage-mitigating control systems design with the following objectives: (1) to achieve high performance with a prolonged life span; and (2) to systematically update the controller as the new technology of advanced materials evolves. The major challenge is to extract the information from the material properties and then utilize this information in a mathematical form so that it can be directly applied to robust control synthesis for mechanical systems. The basic concept of damage-mitigating control is illustrated using a relatively simplified model of a space shuttle main engine.