Modern control system theory and human control functions
Optimal control system theory applied to manual control systems - adaptive control - mathematical models
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Optimal control system theory applied to manual control systems - adaptive control - mathematical models
The present investigation is concerned with a new method, called 'final approach analysis', which has been developed to analyze the dynamic properties of a class of direct adaptive control algorithms. Particular attention is given to the robustness of these algorithms to a number of aspects. These aspects are related to the generation of high frequencies in the plant control signal, to excessive bandwidth of the adaptive control loop resulting in excitation of unmodeled dynamics, and, consequently, leading to dynamic instability of the closed-loop adaptive system, and, thirdly, to noise corrupted measurements. The final approach analysis is useful because it can be used in a constructive way to adjust the adaptive gains so as to limit the closed-loop system bandwidth and to ameliorate some of the undesirable characteristics of existing adaptive algorithms.
A system for assessing vestibulo-ocular function includes a motion sensor system adapted to be coupled to a user's head; a data processing system configured to communicate with the motion sensor system to receive the head-motion signals; a visual display system configured to communicate with the data processing system to receive image signals from the data processing system; and a gain control device arranged to be operated by the user and to communicate gain adjustment signals to the data processing system.
A new nonlinear stability criterion is developed by use of a class of Lyapunov functionals for model-reference adaptive systems (MRAS). Results are compared with traditional results, and a comparative design technique is used to illustrate its function in improving the transient response of an MRAS controller. For a particular system structure and class of input signals, the new stability criterion is shown to include traditional sufficiency stability conditions as a special case. An example is cited to illustrate the use of the nonlinear criterion and its definite advantages in helping improve the adaptive error transient response of a system. Analysis of results is effected by use of a linearization technique on the resulting adaptive equations.
Theoretical and experimental research summaries on suboptimal self-adaptive binary communication systems
Adaptive networks can sense and adjust to dynamic environments to optimize their performance. Understanding their nanoscale responses to external stimuli is essential for applications in nanodevices and neuromorphic computing. However, it is challenging to image such responses on the nanoscale with crystallographic sensitivity. Here, the evolution of nanodomain networks in (PbTiO 3 ) n /(SrTiO 3 ) n superlattices (SLs) is directly visualized in real space as the system adapts to ultrafast repetitive optical excitations that emulate controlled neural inputs. The adaptive response allows the system to explore a wealth of metastable states that are previously inaccessible. Their reconfiguration and competition are quantitatively measured by scanning x-ray nanodiffraction as a function of the number of applied pulses, in which crystallographic characteristics are quantitatively assessed by assorted diffraction patterns using unsupervised machine-learning methods. The corresponding domain boundaries and their connectivity are drastically altered by light, holding promise for light-programable nanocircuits in analogy to neuroplasticity. Phase-field simulations elucidate that the reconfiguration of the domain networks is a result of the interplay between photocarriers and transient lattice temperature. The demonstrated optical control scheme and the uncovered nanoscopic insights open opportunities for the remote control of adaptive nanoscale domain networks.
A walking robot was designed, analyzed, and tested as an intelligent, mobile, and a terrain adaptive system. The robot's design was an application of existing technologies. The design of the six legs modified and combines well understood mechanisms and was optimized for performance, flexibility, and simplicity. The body design incorporated two tripods for walking stability and ease of turning. The electrical hardware design used modularity and distributed processing to drive the motors. The software design used feedback to coordinate the system and simple keystrokes to give commands. The walking machine can be easily adapted to hostile environments such as high radiation zones and alien terrain. The primary goal of the leg design was to create a leg capable of supporting a robot's body and electrical hardware while walking or performing desired tasks, namely those required for planetary exploration. The leg designers intent was to study the maximum amount of flexibility and maneuverability achievable by the simplest and lightest leg design. The main constraints for the leg design were leg kinematics, ease of assembly, degrees of freedom, number of motors, overall size, and weight.
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.
This paper describes the kernel of a distributed operating system called ADAPT. The system runs on top of existing single host operating systems that are networked together. It's purpose is to transform this network of individual systems into a single system that will be easier for application programmers to use. This single system need not be monolithic; ADAPT facilitates the construction of both integrated and modular distributed systems.
F-15 IFCS project goals are: a) Demonstrate Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions [A] & [B] failures. b) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs with a Pilot in the Loop. Gen II objectives include; a) Implement and Fly a Direct Adaptive Neural Network Based Flight Controller; b) Demonstrate the Ability of the System to Adapt to Simulated System Failures: 1) Suppress Transients Associated with Failure; 2) Re-Establish Sufficient Control and Handling of Vehicle for Safe Recovery. c) Provide Flight Experience for Development of Verification and Validation Processes for Flight Critical Neural Network Software.
Recently, electromagnetic suspension systems have become more popular in passenger vehicles. They are superior alternatives to existing conventional passive hydraulic suspension systems. The objective in this paper is to design a new adaptive, not reactive, electromagnetic suspension system. This is performed through two fixed permanent magnets and one electromagnet system packaged as a bolt solution for vehicles. Once combined with other sensors in the vehicle, the proposed electromagnetic system can provide the first fully adaptive suspension system in vehicles.
Algae cultivation systems and methods account for weather variations that can affect algae cultivation. In one system, an open raceway algae cultivation system includes a channel having a high section and a low liquid collection section. The channel is sloped to allow substantially all of an algae cultivation fluid in the high section to flow downwardly into the low liquid collection section. A barrier is removably positioned in the high section and a drain is positioned in the high section such that, when substantially all of the algae cultivation fluid has collected in the low liquid collection section, any rainwater that falls in the high section flows into the drain, without the rainwater mixing with the algae cultivation fluid in the low liquid collection section.
Are the oceans turning into deserts? Rising temperature, increasing surface stratification, and decreasing vertical inputs of nutrients are expected to cause an expansion of warm, nutrient deplete ecosystems. Such an expansion is predicted to negatively affect a trio of key ocean biogeochemical features: phytoplankton biomass, primary productivity, and carbon export. However, phytoplankton communities are complex adaptive systems with immense diversity that could render them at least partially resilient to global changes. This can be illustrated by the biology of the Prochlorococcus “collective.” Adaptations to counter stress, use of alternative nutrient sources, and frugal resource allocation can allow Prochlorococcus to buffer climate-driven changes in nutrient availability. In contrast, cell physiology is more sensitive to temperature changes. We argue that biogeochemical models need to consider the adaptive potential of diverse phytoplankton communities. However, a full understanding of phytoplankton resilience to future ocean changes is hampered by a lack of global biogeographic observations to test theories. We propose that the resilience may in fact be greater in oligotrophic waters than currently considered with implications for future predictions of phytoplankton biomass, primary productivity, and carbon export.
Growth in the intelligence of space systems requires the use and integration of data from multiple sensors. Generic tools are being developed for extracting and integrating information obtained from multiple sources. The full spectrum is addressed for issues ranging from data acquisition, to characterization of sensor data, to adaptive systems for utilizing the data. In particular, there are three major aspects to the project, multisensor processing, an adaptive approach to object recognition, and distributed sensor system integration.
NASA scientists in MDRS Crew 49 (April 23-May 7, 2006) field tested and significantly extended a prototype monitoring and advising system that integrates power system telemetry with a voice commanding interface. A distributed, wireless network of functionally specialized agents interacted with the crew to provide alerts (e.g., impending shut-down of inverter due to low battery voltage), access md interpret historical data, and display troubleshooting procedures. In practical application during two weeks, the system generated speech over loudspeakers and headsets lo alert the crew about the need to investigate power system problems. The prototype system adapts the Brahms/Mobile Agents toolkit to receive data from the OneMeter (Brand Electronics) electric metering system deployed by Crew 47. A computer on the upper deck was connected to loudspeakers, four others were paired with wireless (Bluetooth) headsets that enabled crew members to interact with their personal agents from anywhere in the hab. Voice commands and inquiries included: 1. What is the {battery | generator} {volts | amps | volts and amps}? 2. What is the status of the {generator | inverter | battery | solar panel}? 3. What is the hab{itat} {power usage | volts | voltage | amps | volts and amps}? 4. What was the average hab{itat} {amps | volts | voltage} since <#> {AM | PM)? 5. When did the {generator | batteries} change status? 6. Tell {me I | everyone} when{ ever} the generator goes offline. 7. Tell {me | | everyone} when the hab{itat} {amps | volts | voltage} {exceeds | drops brelow} <#>. 8. {Send | Take | Record} {a} voice note {(for | to} } {at }. This research demonstrates the principles of design in the context of use, investigating requirements through experimental use of prototype systems in an analog setting, and use of MDRS as a research facility for designing and implementing new systems.
The dynamics of the reaction of the hypothalamus-hypophysis-adrenal system to g-forces of 4 G's magnitude reveal a phasal nature of the adaptational system, dependent both on duration of force and position of the body.
This paper presents a comprehensive digital twin (DT) framework for hydroelectric systems that enables adaptive control of turbine governors and excitation systems without requiring detailed manufacturer specifications. The proposed framework integrates neural network-based system identification with stabilizing adaptive control laws for the installed turbine controller and middle-branch adaptive tuning for the installed voltage regulator. Using real operational data from Unit C-8 at Rocky Reach Dam (1,349 MW capacity), highfidelity neural network models are developed to capture turbine and generator dynamics without requiring detailed manufacturer specifications. The DT enables safe controller synthesis and validation in simulation before deployment. For turbine control, the proposed method achieves a 79.9% mean square error (MSE) reduction compared with that of an optimal controller. For voltage regulation, the adaptive excitation controller achieves approximately 42.6% MSE reduction while preserving installed protection logic. The results demonstrate that DT technology provides a practical pathway for modernizing hydropower control systems with minimal operational disruption.
Flight tests to determine reliability of X-15 self adaptive flight control system