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At least 991 records · Page 55

Real-time operational planning for the U.S. air traffic system

This paper describes an integrated planning model for the U.S. air traffic system. The approach incorporates the dual objectives of monitoring collision risk while minimizing transportation costs. Specialized solution algorithms exploit the underlying structure of the model - especially for large-scale examples. The proposed formulation is tested with real-world data for the Indianapolis control sector. Additional experiments with a CRAY X-MP/24 supercomputer show that a full-scale model can be solved under real time conditions. Despite these advances, additional work is required in developing a practical system. Suggestions are made for combining advances in computer graphics and mathematical modeling.

Mulvey, John M.↗

Automatic Detection of Electric Power Troubles (ADEPT)

ADEPT is an expert system that integrates knowledge from three different suppliers to offer an advanced fault-detection system, and is designed for two modes of operation: real-time fault isolation and simulated modeling. Real time fault isolation of components is accomplished on a power system breadboard through the Fault Isolation Expert System (FIES II) interface with a rule system developed in-house. Faults are quickly detected and displayed and the rules and chain of reasoning optionally provided on a Laser printer. This system consists of a simulated Space Station power module using direct-current power supplies for Solar arrays on three power busses. For tests of the system's ability to locate faults inserted via switches, loads are configured by an INTEL microcomputer and the Symbolics artificial intelligence development system. As these loads are resistive in nature, Ohm's Law is used as the basis for rules by which faults are located. The three-bus system can correct faults automatically where there is a surplus of power available on any of the three busses. Techniques developed and used can be applied readily to other control systems requiring rapid intelligent decisions. Simulated modelling, used for theoretical studies, is implemented using a modified version of Kennedy Space Center's KATE (Knowledge-Based Automatic Test Equipment), FIES II windowing, and an ADEPT knowledge base. A load scheduler and a fault recovery system are currently under development to support both modes of operation.

Wang, Caroline↗

Multirate digital control system design

Methods for multirate digital control system design are discussed. A simple method for sampling rate selection based on control bandwidths is proposed. Methods for generating a discrete-time state model of a sampled-data plant and a discrete-time equivalent to an analog cost function for a sampled-data plant are described. The succesive loop closures and linear quadratic Gaussian synthesis methods are reviewed, and a constrained optimization synthesis method is introduced. The proposed sampling rate selection, discretization, and synthesis methods are applied to two example design problems. Multirate and single-rate compensators synthesized by the different methods are compared, based on closed-loop responses, with compensators having the same real-time computation load.

Berg, Martin C.↗

A weak Hamiltonian finite element method for optimal guidance of an advanced launch vehicle

A temporal finite-element method based on a mixed form of the Hamiltonian weak principle is presented for optimal control problems. The mixed form of this principle contains both states and costates as primary variables, which are expanded in terms of nodal values and simple shape functions. Time derivatives of the states and costates do not appear in the governing variational equation; the only quantities whose time derivatives appear therein are virtual states and virtual costates. Numerical results are presented for an elementary trajectory optimization problem; they show very good agreement with the exact solution along with excellent computational efficiency and self-starting capability. The feasibility of this approach for real-time guidance applications is evaluated. A simplified model for an advanced launch vehicle application that is suitable for finite-element solution is presented.

Hodges, Dewey H.↗

Human task animation from performance models and natural language input

Graphical manipulation of human figures is essential for certain types of human factors analyses such as reach, clearance, fit, and view. In many situations, however, the animation of simulated people performing various tasks may be based on more complicated functions involving multiple simultaneous reaches, critical timing, resource availability, and human performance capabilities. One rather effective means for creating such a simulation is through a natural language description of the tasks to be carried out. Given an anthropometrically-sized figure and a geometric workplace environment, various simple actions such as reach, turn, and view can be effectively controlled from language commands or standard NASA checklist procedures. The commands may also be generated by external simulation tools. Task timing is determined from actual performance models, if available, such as strength models or Fitts' Law. The resulting action specification are animated on a Silicon Graphics Iris workstation in real-time.

Esakov, Jeffrey↗

Quiet mode for nonlinear rotor models

High frequency harmonics are generated by helicopter rotor systems, and nonlinear blade-element models of these systems create the same harmonics. In discrete real-time rotorcraft simulation, however, especially for handling qualities research, they are more of a nuisance than a benefit. The cycle times required to adequately represent them are rarely obtainable. The result is that distinct frequencies alias into the pilot and simulator bandwidths, thereby decreasing simulation fidelity. However, use of an interpolation procedure permits the observation of harmonics at their proper frequency locations, and an accompanying notch filter may then be used to attenuate the harmonics prior to decimation. Rotorcraft simulations using these techniques are not contaminated with the spurious frequencies that create variable trim points, produce erroneous stability and control derivative data, and obscure time histories.

Mcfarland, R. E.↗

A finite element based method for solution of optimal control problems

A temporal finite element based on a mixed form of the Hamiltonian weak principle is presented for optimal control problems. The mixed form of this principle contains both states and costates as primary variables that are expanded in terms of elemental values and simple shape functions. Unlike other variational approaches to optimal control problems, however, time derivatives of the states and costates do not appear in the governing variational equation. Instead, the only quantities whose time derivatives appear therein are virtual states and virtual costates. Also noteworthy among characteristics of the finite element formulation is the fact that in the algebraic equations which contain costates, they appear linearly. Thus, the remaining equations can be solved iteratively without initial guesses for the costates; this reduces the size of the problem by about a factor of two. Numerical results are presented herein for an elementary trajectory optimization problem which show very good agreement with the exact solution along with excellent computational efficiency and self-starting capability. The goal is to evaluate the feasibility of this approach for real-time guidance applications. To this end, a simplified two-stage, four-state model for an advanced launch vehicle application is presented which is suitable for finite element solution.

Bless, Robert R.↗

Real-time adaptive aircraft scheduling

One of the most important functions of any air traffic management system is the assignment of ground-holding times to flights, i.e., the determination of whether and by how much the take-off of a particular aircraft headed for a congested part of the air traffic control (ATC) system should be postponed in order to reduce the likelihood and extent of airborne delays. An analysis is presented for the fundamental case in which flights from many destinations must be scheduled for arrival at a single congested airport; the formulation is also useful in scheduling the landing of airborne flights within the extended terminal area. A set of approaches is described for addressing a deterministic and a probabilistic version of this problem. For the deterministic case, where airport capacities are known and fixed, several models were developed with associated low-order polynomial-time algorithms. For general delay cost functions, these algorithms find an optimal solution. Under a particular natural assumption regarding the delay cost function, an extremely fast (O(n ln n)) algorithm was developed. For the probabilistic case, using an estimated probability distribution of airport capacities, a model was developed with an associated low-order polynomial-time heuristic algorithm with useful properties.

Kolitz, Stephan E.↗

Discrete-time adaptive control of robot manipulators

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that asymptotic trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation.

Tarokh, M.↗

A discrete-time adaptive control scheme for robot manipulators

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

Tarokh, M.↗

Real-time fuzzy inference based robot path planning

This project addresses the problem of adaptive trajectory generation for a robot arm. Conventional trajectory generation involves computing a path in real time to minimize a performance measure such as expended energy. This method can be computationally intensive, and it may yield poor results if the trajectory is weakly constrained. Typically some implicit constraints are known, but cannot be encoded analytically. The alternative approach used here is to formulate domain-specific knowledge, including implicit and ill-defined constraints, in terms of fuzzy rules. These rules utilize linguistic terms to relate input variables to output variables. Since the fuzzy rulebase is determined off-line, only high-level, computationally light processing is required in real time. Potential applications for adaptive trajectory generation include missile guidance and various sophisticated robot control tasks, such as automotive assembly, high speed electrical parts insertion, stepper alignment, and motion control for high speed parcel transfer systems.

Pacini, Peter J.↗

Transportable telemetry workstation

The goal was to complete the design of a prototype for a Transportable Telemetry Workstation (TTW). The Macintosh 2 is used to provide a low-cost system which can house real-time cards mounted on the NuBus inside the Macintosh 2 plus provide a standardized user interface on the Macintosh 2 console. Prior to a telemetry run, the user will be able to configure his real-time telemetry processing functions from the Macintosh 2 console. During a telemetry run, the real-time cards will store the telemetry data directly on a hard disk while permitting viewing of the data cards on the Macintosh 2 console on various selectable formats. The user will view the cards in terms of the functions they perform and the selectable paths through the cards, it is not required to become involved directly in hardware issue except in terms of the functional configuration of the system components. The TTW will accept telemetry data from an RS422 serial input data bus, pass it through a frame synchronizer card and on to a real time controller card via a telemetry backplane bus. The controller card will then route the data to a hard disk through a SCSI interface, and/or to a user interface on the Macintosh 2 console by way of the Macintosh 2 NuBus. The three major components to be designed, therefore, are the TTW Controller Card, the TTW Synchronizer Card, and the NuBus/Macintosh 2 User Interface. Design and prototyping of this state-of-the-art, transportable, low-cost, easy-to-use multiprocessor telemetry system is continuing. Other functions are planned for the future.

Collins, Aaron S.↗

Flight control system design factors for applying automated testing techniques

The principal design features and operational experiences of the X-29 forward-swept-wing aircraft and F-18 high alpha research vehicle (HARV) automated test systems are discussed. It is noted that operational experiences in developing and using these automated testing techniques have highlighted the need for incorporating target system features to improve testability. Improved target system testability can be accomplished with the addition of nonreal-time and real-time features. Online access to target system implementation details, unobtrusive real-time access to internal user-selectable variables, and proper software instrumentation are all desirable features of the target system. Also, test system and target system design issues must be addressed during the early stages of the target system development. Processing speeds of up to 20 million instructions/s and the development of high-bandwidth reflective memory systems have improved the ability to integrate the target system and test system for the application of automated testing techniques. It is concluded that new methods of designing testability into the target systems are required.

Sitz, Joel R.↗

Edge smoothing for real-time simulation of a polygon face object system as viewed by a moving observer

The visual system within an aircraft flight simulation system receives flight data and terrain data which is formated into a buffer memory. The image data is forwarded to an image processor which translates the image data into face vertex vectors Vf, defining the position relationship between the vertices of each terrain object and the aircraft. The image processor then rotates, clips, and projects the image data into two-dimensional display vectors (Vd). A display generator receives the Vd faces, and other image data to provide analog inputs to CRT devices which provide the window displays for the simulated aircraft. The video signal to the CRT devices passes through an edge smoothing device which prolongs the rise time (and fall time) of the video data inversely as the slope of the edge being smoothed. An operational amplifier within the edge smoothing device has a plurality of independently selectable feedback capacitors each having a different value. The values of the capacitors form a series which doubles as a power of two. Each feedback capacitor has a fast switch responsive to the corresponding bit of a digital binary control word for selecting (1) or not selecting (0) that capacitor. The control word is determined by the slope of each edge. The resulting actual feedback capacitance for each edge is the sum of all the selected capacitors and is directly proportional to the value of the binary control word. The output rise time (or fall time) is a function of the feedback capacitance, and is controlled by the slope through the binary control word.

Lotz, Robert W.↗

Enhancing Security and Resiliency in Operational Technology Environments Through Network Slicing and Federated Learning

The growing convergence of Information Technology (IT) and Operational Technology (OT) within Industry 4.0 environments has introduced new demands on industrial network infrastructure. As cyber-physical systems become increasingly interconnected, ensuring the secure, timely, and efficient exchange of critical data is essential. This thesis explores how network slicing, a method of creating isolated virtual network segments, can be applied within OT environments to address challenges such as latency, security, and resource allocation. The first research question addressed in this thesis is: How can OT networks take advantage of NFV and SDN technology to become cyber resilient? This study examines the operational, security, and architectural implications of introducing network slicing into traditionally static OT infrastructures such as Industrial Control Systems (ICS) and SCADA. Through simulated deployments and case studies, the research demonstrates how slicing enables better isolation between critical and non-critical services, thereby improving response time, throughput, and security in sensitive environments. The second question considers: How to dynamically implement network slicing and take advantage of network resources towards integrating decentralized machine learning? In response, this thesis proposes a framework that combines Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Federated Learning (FL) to enable real-time analytics while maintaining data locality. The proposed approach reduces the burden on centralized infrastructure and minimizes privacy risks by supporting on-site training of models across distributed OT nodes, coordinated through dynamically allocated network slices. The third focus explores: How slicing helps to increase the resiliency of OT networks through the orchestration of a dynamic DMZ? To answer this, the thesis presents a method for creating and managing Dynamic Demilitarized Zones (DMZs) using network slicing. This enables flexible and automated isolation of sensitive subsystems during threat scenarios or high-risk operations. Coupled with intelligent orchestration and containerized security services, the dynamic DMZ significantly enhances the system's ability to respond to cyber incidents without halting production. Ultimately, this thesis contributes a comprehensive architecture that blends network slicing with machine learning, secure segmentation, and automation, paving the way for resilient, adaptive, and intelligent OT environments. Performance evaluations across multiple scenarios show improvements in system reliability, threat response time, model accuracy, and resource utilization, providing a strong foundation for future industrial automation systems.

Rodiles Delgado, Brian G↗

A Fast Dynamic Internal Predictive Power Scheduling Approach for Power Management in Microgrids: Preprint

This paper presents a Dynamic Internal Predictive Power Scheduling (DIPPS) approach for optimizing power management in microgrids, particularly focusing on external power exchanges among diverse prosumers. DIPPS utilizes a dynamic objective function with a time-varying binary parameter to control the timing of power transfers to the external grid, facilitated by efficient usage of energy storage for surplus renewable power. The microgrid power scheduling problem is modeled as a mixed-integer nonlinear programming (MINLP-PS) and subsequently transformed into a mixed-integer linear programming (MILPPS) optimization through McCormick's relaxation to reduce computational complexity. A predictive window window with 6 data points is solved at an average of 0.92s, a 97.6% improvement over the 38.27s required for the MINLP-PS formulation, implying the numerical feasibility of the DIPPS approach for real-time implementation. Finally, the approach is validated against a static objective using real-world load data across three case studies with different time-varying parameters, demonstrating the ability of DIPPS to optimize power exchanges and efficiently utilize distributed resources while shifting the external power transfers to specified time durations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Exploring the Use of Large Immersive Display Systems in the Nuclear Industry

Large immersive display systems play a critical role in the nuclear industry by enabling advanced training, design reviews, scientific visualization, and safety simulations. These systems, such as CAVE and powerwalls, allow engineers and operators to interact with virtual nuclear environments in real-time, providing a deeper understanding of complex systems. Their ability to simulate real-world scenarios for testing and optimization in a safe, controlled environment ensures that operators and engineers can refine process, enhance safety protocols, and troubleshoot complex challenges. This article outlines key lessons learned from deploying these systems, practical insights into their applications, and considerations for future improvements, aiming to guide their broader adoption and effective use in the nuclear industry.

99 - GENERAL AND MISCELLANEOUS↗

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).

Ding, Zixin [Chicago U.]↗