Abstract: To efficiently determine cross tabulation while keeping confidentiality. A flag conversion unit (11) converts a format of a share of a flag that represents a boundary between groups. A boundary number setting unit (12) generates a share of a vector in which the next element number is set when the flag representing a group boundary is true and the number of records is set when the flag is false. A sorting unit (13) generates a share of a sorted vector which has been sorted by a permutation that moves vectors such that the last elements of each group are sequentially arranged from beginning A count calculation unit (14) sets a difference between the value of one element and the value of the preceding element in the sorted vector and generates a share of a vector representing the number of records in each group.

Abstract: A model receives a target demand curve as an input and outputs an optimized control sequence that allows equipment within a physical space to be run optimally. A thermodynamic model is created that represents equipment within the physical space, with the equipment being laid out as nodes within the model according to the equipment flow in the physical space. The equipment activation functions comprise equations that mimic equipment operation. Values flow between the nodes similarly to how states flow between the actual equipment. The model is run such that a control sequence is used as input into the neural network; the neural network outputs a demand curve which is then checked against the target demand curve. Machine learning methods are then used to determine a new control sequence. The model is run until a goal state is reached.

Abstract: A method for online authoring of robot autonomy applications includes receiving sensor data of an environment about a robot while the robot traverses through the environment. The method also includes generating an environmental map representative of the environment about the robot based on the received sensor data. While generating the environmental map, the method includes localizing a current position of the robot within the environmental map and, at each corresponding target location of one or more target locations within the environment, recording a respective action for the robot to perform. The method also includes generating a behavior tree for navigating the robot to each corresponding target location and controlling the robot to perform the respective action at each corresponding target location within the environment during a future mission when the current position of the robot within the environmental map reaches the corresponding target location.

Abstract: An artificial neural network (ANN) system includes a processor, a virtual overflow detection circuit and a data format controller. The processor performs node operations with respect to a plurality of nodes included in each layer of an ANN to obtain a plurality of result values of the node operations and performs a quantization operation on the obtained plurality of result values based on a k-th fixed-point format for a current quantization of the each layer to obtain a plurality of quantization values. The virtual overflow detection circuit generates a virtual overflow information indicating a distribution of valid bit numbers of the obtained plurality of quantization values. The data format controller determines a (k+1)-th fixed-point format for a next quantization of the each layer based on the generated virtual overflow information. An overflow and/or an underflow are prevented efficiently by controlling the fixed-point format using the virtual overflow.

Abstract: A method and a system for converting a variable delay in real number modeling code to cycle-driven simulation interface event for digital/mixed signal emulation is provided. The method comprises identifying a variable delay of an analog signal in real number modeling code defining an analog circuit; determining a frequency and a maximum number of cycles for a series of discrete clock cycles, wherein the variable delay corresponds to one cycle in the series of discrete clock cycles; converting the variable delay into a plurality of cycle-driven discrete events based on the series of discrete clock cycles; and generating synthesizable code based on the plurality of cycle-driven discrete events for digital mixed signal emulation. A system and a non-transitory computer readable medium to perform the above method are also provided.

Abstract: A control method based on an adaptive neural network model for dissolved oxygen of an aeration system includes: obtaining related water quality monitoring data of a sewage treatment plant, and performing data preprocessing on the related water quality monitoring data; performing principal component analysis on the preprocessed related water quality monitoring data and a dissolved oxygen concentration of the aeration system through a principal component analysis method, and determining a water quality parameter with a highest rate of contribution to a principal component; taking the water quality parameter with the highest rate of contribution to the principal component, and predicting a dissolved oxygen concentration of the aeration system; and optimizing a dissolved oxygen predictive value obtained by means of the adaptive neural network model to obtain an optimal regulation value, and performing online regulation on a fuzzy control system of the adaptive neural network model.

Abstract: A system and method including determining, for a specified target measure column of a first dataset including a plurality of records, the metadata of the first dataset, including a probability distribution for the specified target column and dimension scores for the dimensions for the first dataset conditioned on the specified target measure column, where the first dataset comprises a plurality of columns including the at least one target measure column and a plurality of non-numeric, dimension columns for the records of the first dataset; determining, for a subset of data of the first dataset based on one or more specified variables, dimension scores for the dimensions of the subset of data approximately derived from the determined metadata of the first dataset; and providing recommendations of top contributors based on the approximated dimension scores of dimensions of the subset of data.

Abstract: Provided herein are a method of extracting a feature from an image using a laser pattern and an identification device and a robot including the same, and the identification device for extracting a feature from an image using a laser pattern, which includes a first camera coupled to a laser filter and configured to generate a first image including a pattern of a laser which is reflected from an object, a second camera configured to capture an area overlapping an area captured by the first camera to generate a second image, and a controller configured to generate a mask for distinguishing an effective area using the pattern included in the first image and extract a feature from the second image by applying the mask to the second image.

Abstract: The present invention relates to a system for mapping external inputs and internal goals toward actions that solve problems or elicit external rewards. The present invention allows an instructor to test and train an agent to perform dynamic task selection (executive control) by using a schema that computes the agent's emotional and motivational states from reward/punishment inputs and sensory inputs (visual, auditory, kinematic, tactile, olfactory, somatosensory, and motor inputs). Specifically, the invention transforms the sensory inputs into unimodal and bimodal spatio-temporal schemas that are combined with the reward/punishment inputs and with the emotional and motivation states to create an external/internal schema (EXIN schema), that provides a compressed representation assessing the agent's emotions, motivations, and rewards. The invention uses the EXIN schema to create a motor schema to be executed by the agent to dynamically perform the task selected by the instructor.

Abstract: In one or more embodiments, a weldability of a stack-up for use in vehicle part production may be determined. The determination may include receiving general stack-up information, welding standards data for forming a stack-up, and one or more inputs defining one or more stack-up design variables. Additionally, standardized stack-up information may be generated based on the general stack-up information, the one or more design variables, and the welding standards data. Furthermore, historical welding data may be received for predicting a weldability of the stack-up. Predictive logic may be applied to the standardized stack-up information based on the historical welding data to obtain one or more weldability predictions for the stack-up. The one or more weldability predictions may be transmitted for use in vehicle part production.

Abstract: An autonomous floor cleaning robot includes a transport drive and control system arranged for autonomous movement of the robot over a floor for performing cleaning operations. The robot chassis carries a first cleaning zone comprising cleaning elements arranged to suction loose particulates up from the cleaning surface and a second cleaning zone comprising cleaning elements arraigned to apply a cleaning fluid onto the surface and to thereafter collect the cleaning fluid up from the surface after it has been used to clean the surface. The robot chassis carries a supply of cleaning fluid and a waste container for storing waste materials collected up from the cleaning surface.

Abstract: Generally, decisions are based on information. To be useful, information must be reliable. Basically, the concept of a Z-number relates to the issue of reliability of information. A Z-number, Z, has two components, Z=(A,B). The first component, A, is a restriction (constraint) on the values which a real-valued uncertain variable, X, is allowed to take. The second component, B, is a measure of reliability (certainty) of the first component. Typically, A and B are described in a natural language, for example: (about 45 minutes, very sure). Z-number has many applications, especially in the realms of economics, decision analysis, risk assessment, prediction, anticipation, rule-based characterization of imprecise functions and relations, and biomedicine. Different methods, applications, and systems are discussed. Other Fuzzy concepts are also discussed.

Abstract: Various amounts of information can be beneficial to different controllers configured upon an industrial control system. Information can be retained in a distributed directory such that controllers quickly learn information concerning other controllers. The distributed directory can be automatically constructed and populated with information from different controllers. When a module enters an industrial control system, information can automatically advertise to other units through use of the distributed directory.

Abstract: The control optimization method for helicopters carrying suspended loads during hover flight utilizes a controller based on time-delayed feedback of the load swing angles. The controller outputs include additional displacements, which are added to the helicopter trajectory in the longitudinal and lateral directions. This simple implementation requires only a small modification to the software of the helicopter position controller. Moreover, the implementation of this controller does not need rates of the swing angles. The parameters of the controllers are optimized using the method of particle swarms by minimizing an index that is a function of the history of the load swing. Simulation results show the effectiveness of the controller in suppressing the swing of the slung load while stabilizing the helicopter.

Abstract: The fuzzy logic-based control method for helicopters carrying suspended loads utilizes a controller based on fuzzy logic membership distributions of sets of load swing angles. The anti-swing controller is fuzzy-based and has controller outputs that include additional displacements added to the helicopter trajectory in the longitudinal and lateral directions. This simple implementation requires only a small modification to the software of the helicopter position controller. The membership functions govern control parameters that are optimized using a particle swarm algorithm. The rules of the anti-swing controller are derived to mimic the performance of a time-delayed feedback controller. A tracking controller stabilizes the helicopter and tracks the trajectory generated by the anti-swing controller.

Abstract: In a method for managing a data center, data for a training set of data is collected. The data includes heat loads generated by a plurality of electronic components and temperatures at multiple locations in the data center and under varying power profiles. A machine learning application is implemented to develop a model of a thermal topology of the data center using the training set of data and the model is implemented to predict heat profiles corresponding to a plurality of power profiles that are outside of the training set of data.

Abstract: A method of controlling a process driven by a control signal for producing a corresponding output includes producing an error signal as a function of a state of the process and of a reference signal. A control signal is generated as a function of the error signal and of a parameter adjustment signal. The control signal is applied to the process. A derived signal representative of a quantity to be minimized is calculated by processing paired values of the state of the process and the control signal. A correction signal is calculated from a set of several different values of the control signal that minimizes the derived signal. The parameter adjustment signal is calculated by a neural network and fuzzy logic processor from the error signal and the correction signal. The correction signal is periodically calculated by a Quantum Genetic Search Algorithm that results from a merging of a genetic algorithm and a quantum search algorithm.

Abstract: A system and method for implementing an indirect controller for a plant. A plant can be provided with both a direct controller and an indirect controller with a system model or a committee of system models. When the system model has sufficient integrity to satisfy the plant requirements, i.e., when the system model has been sufficiently trained, the indirect controller with the system model is automatically enabled to replace the direct controller. When the performance falls, the direct controller can automatically assume operation of the plant, preferably maintaining operation in a control region suitable for generating additional training data for the system model. Alternatively, the system model incorporates a committee of models. Various types of sources for errors in the committee of models can be detected and used to implement strategies to improve the quality of the committee.

Abstract: The present invention provides a method of optimizing a painting process for applying a paint layer on an article. The method comprises defining a functional relationship paint processing parameters and a paint layer property (i.e., the average paint layer thickness) using a neural network. This functional relationship is then used in a paint optimization function that measures a combination of quality control parameters and efficiency parameters. Finally, the paint optimization function is optimized by adjusting the paint processing parameters utilizing the functional relationship formed by the neural network. The invention also provides a system that implements the methods of the invention.

Abstract: In tuning a controller for a process in a feedback control system, a method is provided for bringing the system into asymmetric self-excited oscillations for measuring the frequency of the oscillations, average over the period value of the process output signal and average over the period control signal and tuning the controller in dependence of the measurements obtained. An element having a non-linear characteristic is introduced into the system in series with the process and set point signal is applied to excite asymmetric self-excited oscillations in the system. An algorithm and formulas are given for identification of the process model having the form of first order plus dead time transfer function. PI controller settings are given as a function of the dead time/time constant ratio. An apparatus for performing the method is disclosed.

Abstract: A method for determining an output value having a known relationship to an input value with a predicted value includes the step of first training a predictive model with at least one output for a given set of inputs that exist in a finite dataset. Data is then input to the predictive model that is within the set of given inputs. Thereafter, a prediction is made of an output from the predictive model that corresponds to the given input such that a predicted output value will be obtained which will have associated therewith the errors of the predictive model.

Abstract: An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Abstract: Intelligent logic activity resolution (ILAR) is provided for a process. Upon a first trigger event being received, a first subset of conditions of the process is detected. The first subset of conditions is selected based on the first trigger event. When the first subset of conditions match predetermined values, a first state is entered. When the first subset conditions do not match the predetermined values, additional conditions are checked. On the basis of the checked additional conditions, a new state is selected for entry.

Abstract: It is objective of the invention to provide a highly reliable control apparatus and method which reduces the amount of calculation required for both learning of an input/output relationship and actual control as well as prevent inappropriate outputs from being generated for inputs which have been never learned. According to one aspect of the invention, pairs of an input pattern vector for learning and a target output are distributed to a class based on the target output. Then, a correspondence between each element of the input pattern vector for learning and the target output is learned only in that class, and a distribution function is calculated for distributing a new input pattern vector for learning to that class. After the completion of this learning, the distribution function is used to determine which class a new input pattern vector detected by a sensor belongs to. Finally, an output is calculated according to the learning result of that class.

Abstract: A robust Artificial Neural Network controller is proposed for the motion control of a magnetic disk drive voice coil motor (voice coil motor). The neural controller is used to approximate the nonlinear functions (actuator electromechanical dynamics) of the voice coil motor while having on line training. One main advantage of this approach, when compared with standard adaptive control, is that complex dynamical analysis is not needed. Using this design, not only strong robustness with respect to uncertain dynamics and non-linearities can be obtained, but also the output tracking error between the plant output and the desired reference can asymptotically converge to zero. Additionally, standard offline training, utilizing training vectors to stimulate the voice coil motor, is not required.

Abstract: A neural network construct is trained according to sets of input signals (descriptors) generated by conducting a first experiment. A genetic algorithm is applied to the construct to provide an optimized construct and a CHTS experiment is conducted on sets of factor levels proscribed by the optimized construct.

Abstract: An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Abstract: An intrinsically safe microprocessor controlled pressure regulator for operation in a hazardous environment. The intrinsically safe microprocessor controlled pressure regulator receives control commands that are input to a microprocessor in the hazardous environment. The microprocessor generates control commands to control operation of an intrinsically safe solenoid valve and an intrinsically safe piezo electric valve. The piezo electric valve generates an output signal for controlling operating parameters of the paint gun. One or a plurality of microprocessors may operate within a hazardous environment in order to control one or a plurality of intrinsically safe valves in the hazardous environment.

Abstract: An MFC controlling device automation method and related system. The method mainly comprises the steps of automatically controlled algorithmic obtaining of MFC open loop system parameters by an identification technique; automatically controlled algorithmic determining of PI control parameters by a dominant pole-placement method; and automatically controlled calculating of a fuzzy logic rule table. The steps form an automatically controlled single closed loop. By performing said steps, multiple PI control parameter sets are obtainable fast and in an automatic way, and a calculation is done to form a refined fuzzy rule data table, so that a greatly enhanced MFC reaction function is attained.

Abstract: A fuzzy logic controller system comprising a plurality of fuzzy logic controller units cascadably coupled to one another, each controller having a membership processor for receiving a single input signal corresponding to a sensed parameter from a controlled system and performing fuzzy inference operations based on the input signal for outputting an incremental output signal indicative of a requested change in a controlled output from a current level, a permissions processor for scaling the incremental output signal in response to a fulfillment signal from another controller, a processor responsive to the membership processor and to the permissions processor for providing a fulfillment signal to another controller indicative of a permissible range of freedom for scaling the incremental output signal of the another controller in the cascading sequence, an adder for summing each of the incremental output signals from the plurality of controllers and applying the sum to the controlled output for providing a corre

Abstract: A reduced control system suitable for control of a nonlinear or unstable plant is described. The reduced control system is configured to use a reduced sensor set for controlling the plant without significant loss of control quality (accuracy) as compared to an optimal control system with an optimum sensor set. The control system calculates the information content provided by the reduced sensor set as compared to the information content provided by the optimum set. The control system also calculates the difference between the entropy production rate of the plant and the entropy production rate of the controller. A genetic optimizer is used to tune a fuzzy neural network in the reduced controller. A fitness function for the genetic optimizer provides optimum control accuracy in the reduced control system by minimizing the difference in entropy production while maximizing the sensor information content.

Abstract: A machine control system for controlling an unstable or transition running condition of a machine which is operable by a causative signal and the performance of which is indicatable by an indicative signal. The control system includes: (a) a model-based control unit for outputting an estimated value of a causative signal when receiving an indicative signal, which model-based control unit undergoes learning based on teacher data; (b) a feedback control unit for providing first teacher data to the model-control unit upon receiving feedback information from the machine; and (c) an anticipatory control unit for providing second teacher data to the model-based control unit.

Abstract: The method according to the present invention is used for automatically configuring a fuzzy automatic-control device, in the form of generating transformation criteria. These transformation criteria preferably have change, stop, jump-back and reset rules for the individual states of the fuzzy automatic-control device that represent recognition probabilities. The method allows transformation criteria for configuring fuzzy automatic-control devices to be produced fully automatically by the arithmetic logic unit. Even if the pattern signals change frequently, the fuzzy automatic-control device can thus be reconfigured quickly, flexibly and without complications.

Abstract: An autonomic system for updating a fuzzy neural network includes a process of calculating an estimated value based on fuzzy inference by using a neural network structure, wherein a parameter to be adjusted or identified by fuzzy inference and outputted from the neural network is made to correspond to coupling loads which are updated by learning, i.e., fuzzy rules and membership functions are adjusted by learning. This system is characterized in that the addition and deletion of fuzzy rules are conducted based on changes in output errors in an autonomic manner, thereby effectively obtaining appropriate numbers of fuzzy rules optimal for an object such as a vehicle engine having strong non-linearity. Fuzzy rules are formed by a combination of membership functions representing variables such as an engine speed and a throttle angle.

Abstract: A method for an anaerobic digester system is provided that employs a cumulative data base to better monitor and control the anaerobic process, as compared with conventional anaerobic digester systems. The method includes the storing and ensiling of a feedstock, preferably a biomass, to form a digester feed material, which then processed by a digester. The process evolves a biogas and forms a digested material. The process is monitored, to collect a plurality of digester data from all stages of the process. These individual points or elements of the data are telemetered to a cumulative data base for storage and eventual retrieval and the cumulative data base is mined to compile predictive, feed forward controls and construct feedstock correlations between the metabolic activity within the digesters and an analysis of the feedstocks into the digesters. The method further includes the production of a high quality plant growth media from the digested mash, and recovery of the biogas generated within the digester.

Abstract: The fuzzy inference circuit includes a sensor sensing a state of a control object, and a charge coupled device storing fuzzy rule function values for at least one fuzzy rule function. The charge coupled device further performs a fuzzy inference on output of the sensor using the fuzzy rule function values to generate a control signal for controlling the control object.

Abstract: A malfunction diagnostic and repair guidance system and method wherein a matrix of numbers indicating the state of a complex binary system is used as an input vector for a neural network pattern processing capability that is focused to distinguish malfunction types of patterns. The neural network capability provides two complementary network types to classify and generalize the binary matrix. An interactive operator interface is updated with each repair after the root cause and is proposed repair of a malfunction is identified.

Abstract: A device and a method use a decision-tree induction analysis to determine a web tension ratio range for which web breaks are less likely to occur within a printing system based on web tension data collected from a plurality of previous runs of the printing system. The device and method also measure two are more web tensions during operation of the printing system, calculate a web tension ratio and compare that calculated web tension ratio with the determined web tension ratio range. When the calculated web tension ratio falls outside of the determined web tension ratio range, the device and method alert a user to the fact that a condition leading to a web break is present and/or control the measured web tensions to drive the calculated web tension ratio to be within the determined web tension ratio range.

Abstract: The automated integrated input-output control system apparatus. A versatile industrial control apparatus that can be utilized as a modular unit or integrated into industrial machinery or tools to provide an apparatus and method for programmable control of industrial tools, industrial controls and manufacturing operation processes. The automated integrated input-output control system apparatus includes the following components: a control-power mechanism housing, a sensor, input attachment devices, output attachment device, and a control system.

Abstract: A process control system including a method of suppressing overshoot of a process variable beyond the process value setpoint by predicting the overshoot by observing a waveform associated with the process variable, observing the waveform associated with the process variable, without regard to time scale or to amplitude scale, taking corrective action to reduce or eliminate said overshoot by utilizing a fuzzy logic module with a proportional integral derivative control to take corrective action of the process variable.

Abstract: A control apparatus for controlling a control amount of a control target by changing an operating amount which is supplied to the control target, comprises an adjusting section for calculating an adjustment signal in accordance with the control amount measured by the control target and a target control amount, an operating section for transmitting an operating amount to the control target in accordance with the adjustment signal calculated by the adjusting section, an observation data storing section for storing observation data having control amounts and operating amounts observed previously, and a learning section for learning internal parameters for the adjusting section in accordance with response time taken for the control target from input of the operating amount from the operating section to the control target to appearance of an influence of the operating amount on the control amount and observation data stored in the observation data storing section.

Abstract: A fuzzy control system, particularly for dose rate control in an X-ray diagnostics apparatus, such a control system converting input signals into output signals. A first and a second individual module are provided, whereby respectively at least two input signals can be supplied to the first and to the second individual module for generating an output signal. Compared to a fuzzy control system that does not comprise these individual modules, the rule base becomes smaller, only input conditions that have influence on the individual module need be provided with rules, so that a simple check of the rules for completeness is assured.

Abstract: A dynamical system analyser (10) incorporates a computer (22) to perform a singular value decomposition of a time series of signals from a nonlinear (possibly chaotic) dynamical system (14). Relatively low-noise singular vectors from the decomposition are loaded into a finite impulse response filter (34). The time series is formed into Takens' vectors each of which is projected onto each of the singular vectors by the filter (34). Each Takens' vector thereby provides the co-ordinates of a respective point on a trajectory of the system (14) in a phase space. A heuristic processor (44) is used to transform delayed co-ordinates by QR decomposition and least squares fitting so that they are fitted to non-delayed co-ordinates. The heuristic processor (44) generates a mathematical model to implement this transformation, which predicts future system states on the basis of respective current states. A trial system is employed to generate like co-ordinates for transformation in the heuristic processor (44).

Abstract: A direct adaptive fuzzy controller having an adaptation mechanism that modifies the locations of output membership functions to improve performance of the fuzzy controller. The controller has a fuzzy rule base that has a different or unique output membership function for each fuzzy rule. The adaptation mechanism modifies the location of the output membership functions in response to the performance of the controller system, to continuously improve its performance. The controller is a feedback mechanism that functions not only using measured outputs of the process controlled, but has feedforward compensation that causes the controller to anticipate feedback due to measured disturbances or other parameters of the process.