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Time varying control of CL is necessary for integrating AFC and Flight Control (Biasing allows for +/- changes in lift) Time delays associated with actuation are long (APPROX.5.8 c/U) and must be included in controllers. Convolution of input signal with single pulse kernel gives reasonable prediction of lift response.
The invention provides systems and methods for manipulating biological systems, for example to elicit a more desired biological response from a biological sample, such as a tissue, organ, and/or a cell. In one aspect, the invention operates by efficiently searching through a large parametric space of stimuli and system parameters to manipulate, control, and optimize the response of biological samples sustained in the system. In one aspect, the systems and methods of the invention use at least one optimization algorithm to modify the actuator's control inputs for stimulation, responsive to the sensor's output of response signals. The invention can be used, e.g., to optimize any biological system, e.g., bioreactors for proteins, and the like, small molecules, polysaccharides, lipids, and the like. Another use of the apparatus and methods includes is for the discovery of key parameters in complex biological systems.
An apparatus controls positions of plural mirror segments in a segmented mirror with an edge sensor system and a controller. Current mirror segment edge sensor measurements and edge sensor reference measurements are compared with calculated edge sensor bias measurements representing a global radius of curvature. Accumulated prior actuator commands output from an edge sensor control unit are combined with an estimator matrix to form the edge sensor bias measurements. An optimal control matrix unit then accumulates the plurality of edge sensor error signals calculated by the summation unit and outputs the corresponding plurality of actuator commands. The plural mirror actuators respond to the actuator commands by moving respective positions of the mixor segments. A predetermined number of boundary conditions, corresponding to a plurality of hexagonal mirror locations, are removed to afford mathematical matrix calculation.
Abstract A novel hybrid Model Predictive Control (MPC) algorithm has been designed for simultaneous safety factor ( q ) profile and stored energy ( w ) control while incorporating the pulse-width-modulation constraints associated with the neutral beam injection (NBI) system. Regulation of the q -profile has been extensively shown to be a key factor for improved confinement as well as non-inductive sustainment of the plasma current. Simultaneous control of w is necessary to prevent the triggering of pressure-driven magnetohydrodynamic instabilities as the controller shapes the q profile. Conventional MPC schemes proposed for q -profile control have considered the NBI powers as continuous-time signals, ignoring the discrete-time nature of these actuators and leading in some cases to performance loss. The hybrid MPC scheme in this work has the capability of incorporating the discrete-time actuator dynamics as additional constraints. In nonlinear simulations, the proposed hybrid MPC scheme demonstrates improved q -profile+ w control performance for NSTX-U operating scenarios.
Innovative control configurations using high temperature switches to operate actuator driving solenoids were studied. The impact on engine control system life cycle costs and reliability of electronic control and (ECU) heat dissipation due to power conditioning and interface drivers were addressed. Various power supply and actuation schemes were investigated, including optical signal transmission and electronics on the actuator, engine driven alternator, and inside the ECU. The use of a switching shunt power conditioner results in the most significant decrease in heat dissipation within the ECU. No overall control system reliability improvement is projected by the use of remote high temperature switches for solenoid drivers.
Multi-body flexible structures, such as those currently under investigation in spacecraft design, are large scale (high-order) dimensional systems. Controlling and filtering such structures is a computationally complex problem. This is particularly important when many sensors and actuators are located along the structure and need to be processed in real time. This report summarizes research activity focused on solving the signal processing (that is, information processing) issues of multi-body structures. A distributed architecture is developed in which single loop processors are employed for local filtering and control. By implementing such a philosophy with an embedded controller configuration, a supervising controller may be used to process global data and make global decisions as the local devices are processing local information. A hardware testbed, a position controller system for a servo motor, is employed to illustrate the capabilities of the embedded controller structure. Several filtering and control structures which can be modeled as rational functions can be implemented on the system developed in this research effort. Thus the results of the study provide a support tool for many Control/Structure Interaction (CSI) NASA testbeds such as the Evolutionary model and the nine-bay truss structure.
A method is presented for predicting the amplitude and frequency, under certain simplifying conditions, of the hunting oscillations of an automatically controlled aircraft with lag in the control system or in the response of the aircraft to the controls. If the steering device is actuated by a simple right-left type of signal, the series of alternating fixed amplitude signals occuring during the hunting may ordinarily be represented by a square wave. Formulas are given expressing the response to such a variation of signal in terms of the response to a unit signal.
Interface unit and controller emulator developed for research on electronic helicopter-flight-control systems equipped with artificial intelligence. Interface unit interrupt-driven system designed to link microprocessor-based, quadruply-redundant, asynchronous, ultra-reliable, fault-tolerant control system (controller) with electronic servocontrol unit that controls set of hydraulic actuators. Receives digital feedforward messages from, and transmits digital feedback messages to, controller through differential signal lines or fiber-optic cables (thus far only differential signal lines have been used). Analog signals transmitted to and from servocontrol unit via coaxial cables.
A method is presented for predicting the amplitude and frequency, under certain simplifying conditions, of the hunting oscillations of an automatically controlled aircraft with lag in the control system or in the response of the aircraft to the controls. If the steering device is actuated by a simple right-left type of signal, the series of alternating fixed-amplified signals occurring during the hunting may ordinarily be represented by a "square wave." Formulas are given expressing the response to such a variations of signal in terms of the response to a unit signal. A more complex type of hunting, which may involve cyclic repetition of signals of varying duration, has not been treated and requires further analysis. Several examples of application of the method are included and the results discussed.
A six degree-of-freedom electromagnetically suspended motion control stage (the Angstrom Stage) has been designed and constructed for use in short-travel, high-resolution motion control applications. It achieves better than 0.5 nm resolution over a 100 micron range of travel. The stage consists of a single moving element (the platen) floating in an oil filled chamber. The oil is crucial to the stage's operation since it forms squeeze film dampers between the platen and the frame. Twelve electromagnetic actuators provide the forces necessary to suspend and servo the platen, and six capacitance probes measure its position relative to the frame. The system is controlled using a digital signal processing board residing in a '486 based PC. This digital controller implements a feedback linearization algorithm in real-time to account for nonlinearities in both the magnetic actuators and the fluid film dampers. The feedback linearization technique reduces a highly nonlinear plant with coupling between the degrees of freedom into one that is linear, decoupled, and setpoint independent. The key to this procedure is a detailed plant model. The operation of the feedback linearization procedure is transparent to the outer loop of the controller, and so a proportional controller is sufficient for normal operation. We envision applications of this stage in scanned probe microscopy and for integrated circuit measurement.
Provided are implantable, injectable and/or surface mounted biomedical devices and related methods for interfacing with a target tissue. The devices have a substrate, one or more microfluidic channels embedded in or supported by the substrate and a fluid actuator in operational communication with one or more reservoirs and responsive to a wireless control signal. The components of the device are specially configured and packaged to be ultra-thin and mechanically compliant. In some embodiments, the devices are self-powered and fully implantable. The devices can be shaped to provide injection in a minimally invasive manner, thereby avoiding unnecessary tissue damage and providing a platform for long-term implantation for interfacing with biological tissue.
The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.
The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.
The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface is a state machine, such as an ASIC, that operates independent of a processor in communicating with the bus controller and data channels.
Inter-area oscillation modes usually fall within the same frequency range of 0.1 to 1.0 Hz; thus, power oscillation damping (POD) control methods should avoid unnecessary excitation of weakly damped modes. This paper presents a decoupled control strategy to damp inter-area oscillations in the power grid. Pure oscillation mode signals are extracted from wide-area measurements and used as feedback input for POD actuators such as power system stabilizers or high-voltage direct current transmission. The decoupled control strategy is able to increase the damping of the concerned oscillation modes without deteriorating others. This proposed strategy could be implemented independently, or serve as a complement and work along with conventional POD controllers to damp concerned inter-area modes. The proposed method has been tested on a modied MinniWECC system. Extensive results indicate that inter-area oscillations can be successfully and precisely damped using the proposed decoupled strategy.
Increasing urban mobility requirements demand efficient transportation system strategies for both vehicular and pedestrian movement. This study enhances the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) approach, originally tailored for vehicular traffic signal timing, to incorporate pedestrian traffic dynamics. The improved algorithm considers crucial metrics such as Eco_PI, assesses vehicle fuel consumption by factoring in stops and delays, and addresses pedestrian waiting time, crucial for system efficiency while acknowledging driver waiting time impact. Utilizing Digital Twin simulation along the MLK Smart Corridor in Chattanooga, Tennessee, the algorithm's performance is compared for various pedestrian control scenarios. To evaluate the effectiveness of DGMARL, this study compared DGMARL-enabled signal management with automated pedestrian traffic detection and an actuated signal management system (real-word baseline) with pedestrian recall, which predetermingly enforces a pedestrian phase every cycle. Findings indicate substantial improvements with DGMARL, showing a 28.29% enhancement in vehicle Eco_PI, a 60.55 % reduction in pedestrian waiting time, and a 55.74% decrease in driver stop delay, on average, compared to the baseline actuated signal timing plan.
The concept of analytic redundancy is extended to identify nonzero constant output failures in large spacecraft active control sensors and actuators, using a set of distributed sensors which do not nominally produce equivalent signals but are related through the structural dynamics of the system. The suboptimal technique uses a Sequential Probability Ratio Test on the residual sequence of a Kalman filter based on a modal structure model, to determine failure of a component based on an assumed failure hypothesis. The specific failure is identified and then the Kalman filter gains are reconfigured for the identified remaining working sensor set. Experimental data using an apparatus whose dynamics are representative of a large spacecraft show the nominal filter performance under failed and unfailed conditions.
Optimizing traffic control systems at traffic intersections can reduce network-wide fuel consumption as well as improve traffic flow. While traffic signals have conventionally been controlled based on predetermined schedules, various adaptive control systems have been developed recently using advanced sensors such as cameras, radars, and LiDARs. By utilizing rich traffic information enabled by the advanced sensors, more efficient or optimal traffic signal control is possible in response to varying traffic conditions. This paper proposes an optimal traffic signal control method to minimize network-wide fuel consumption utilizing real-time traffic information provided by advanced sensors. This new method employs a priority metric calculated by a weighted sum of various factors, including the total number of vehicles, total vehicle speed, vehicle waiting time, and road preference. Genetic Algorithm (GA) is used as a global optimization method to determine the optimal weights in the priority metric. In order to evaluate the effectiveness of the proposed method, a traffic simulation model is developed in a high-fidelity traffic simulation environment called SUMO, based on a real-world traffic network. The traffic flow within this model is simulated using actual measured traffic data from the traffic network, enabling a comprehensive assessment of the novel optimal traffic signal control method in realistic conditions. The simulation results show that the proposed priority metric-based real-time traffic signal control algorithm can significantly reduce network-wide fuel consumption compared to the conventional fixed-time control and coordinated actuated control methods that are currently used in the modeled network. Additionally, incorporating truck priority in the priority metric leads to further improvements in fuel consumption reduction.