Abstract: The present invention provides a method and system for representing fuzzy information, and performing fuzzy logic and control operations on that information, using a quantum system. According to one embodiment fuzzy logic and control operations are performed on a quantum computer. The present invention extends quantum information processing beyond purely Boolean-logical information processing, by providing a quantum mechanical method for representing fuzzy information and realizing fuzzy logic and control.

Abstract: A multiple zone electronic control system and method are provided to control a heating, ventilation and air conditioning (HVAC) system for a vehicle. The control system includes a plurality of sensors to provide inputs relating to multiple zones of an occupant compartment of the vehicle and a plurality of buttons to provide manual inputs relating to the multiple zones. The control system also includes a plurality of mechanisms to control temperature and flow of air from the HVAC system into the multiple zones. The control system further includes a controller electrically connected to the sensors and the buttons to receive the inputs therefrom and electrically connected to the mechanisms to control the temperature and flow of air into each of the multiple zones.

Abstract: Neural network architectures are represented by symbol strings. An initial population of networks is trained and evaluated. The strings representing the fittest networks are modified according to a genetic algorithm and the process is repeated until an optimized network is produced.

Abstract: The invention uses fuzzy logic and/or probability distributions to automatically calculate and display the effects of contextual information on the confidence that an object in an image is an object of interest. The goal is to assist in determining the location and type of target objects of interest in that imagery. The imagery can come from any kind of imaging sensor or can be non-sensor imagery (e.g., two-and three-dimensional maps), and can be live or archived imagery. The locations of context objects can be provided by a human or a computer. The resulting set of data, including the original imagery, the locations of context objects, any results from AOD, and predictions about target object type and location, can be combined into a display that helps a human better understand where target object appears in the imagery.

Abstract: A water-in-fuel abuse detection system provides a way to determine if a vehicle operator has ignored a conventional water-in-fuel indicator light and continued to operate the vehicle beyond a certain threshold. The system includes a sensor positioned in a fuel filter capable of separating an amount of water from a source of fuel. The sensor is operatively connected to a software routine, as well as to a conventional indicator light that illuminates to alert a vehicle operator that water must be purged from the fuel filtration system. The software routine determines the duration, in distance traversed or time elapsed, that the amount of water is at or above the level of the sensor. The routine then writes a fault code to permanent memory when the threshold is exceeded. A diagnostic tool can access the permanent memory and reveal whether the fuel system has be the subject of water-in-fuel abuse.

Abstract: This invention proposes a novel nonlinear filter called adaptive weighted fuzzy mean (AWFM) filter which is capable of removing high density Gaussian impulse noises in polluted images. Via a single epoch, weights of the filter are departed according to a set of fuzzy rules, which are constructed by a proposed procedure. All the fuzzy rules in the knowledge base infer concurrently for input nature estimation and filter adaptation. Statistic analyses ensure that this AWFM filtering possesses robust and consistent performance even when images are thoroughly polluted. The AWFM filter is synthesized with generic LR fuzzy cells which adopts CMOS analog current mode technology to subject high speed, low power, and small circuit area objectives. Simulations show that parallel inferences realized by the generic LR fuzzy cells, each of which performs 20 M FLIPS (fuzzy logic inferences per second) promise that the synthesized AWFM filter is able to process up to 50 256×256 images per second.

Abstract: A fuzzy controller (130) for use in target detection systems. The fuzzy controller (130) includes a first circuit (132) for determining a number of false alarms in a frame of data. A second circuit (136) determines a desired number of false alarms for the frame of data. A third circuit (134-152) computes a threshold multiplier factor based on the number of false alarms, the desired number of false alarms, and one or more fuzzy rules. In a specific embodiment, the first circuit (132) includes a target detection system for providing addresses of pixels whose values are within a predetermined range relative to a detection threshold. The second circuit (136) includes an input device (136) for accepting the desired number of false alarms as input to the fuzzy controller (130). The third circuit (138-152) includes a fuzzifier input calculation circuit (134) that computes a fuzzifier input value based on the number of false alarms detected in a frame and the desired number of false alarms.

Abstract: The present invention relates to a data processing system in a hierarchical network configuration for executing applicable data processes in a comprehensible and executable form. An object of the present invention is to allow data processing capabilities to be established with high precision in a short time based on a fuzzy-neuro-integrated concept. A fuzzy model is generated by a data processing system in the form of membership functions and fuzzy rules as technical information relating to a control target. According to this fuzzy model, a weight value of the connection between neurons is set and a pre-wired neural network is established. Then, the data of the control target are learned by the neural network. The connection state and a weight value of the neural network after the learning enable tuning of the fuzzy model.

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 controller for a switched reluctance machine utilizing a feedforward neural network in combination with either a fuzzy logic controller or a proportional-integral controller to provide output control signals (e.g., turn-ON angle, turn-OFF angle and peak current) for controlling the energization of a switched reluctance machine. In an alternate embodiment, a fuzzy logic controller is utilized by itself to control a switched reluctance machine.

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: Method and apparatus of parallel processing of multiple inference rules organized in fuzzy sets or logical functions of multiple fuzzy sets including membership functions defined in a so-called universe of discourse. The inference rules are configured essentially as IF-THEN rules with at least one antecedent preposition and at least one consequent implication. The prepositions have at least one term of comparison between membership functions and a plurality of input data and each term is separated by logical operators. The method associates with the logical operators maximum and minimum operations among two or more elements and calculates exhaustively the overall degree of truth (&OHgr;) of a rule with a maximum or minimum of N partial truth levels. The method is accomplished by a plurality of identical, parallel inferential processors. Each inferential processor determines a preposition or a partial truth level of a preposition.

Abstract: A fuzzy processor with an improved architecture. The fuzzy processor includes a fuzzy rule processor, an internal fuzzy instruction memory, an internal knowledge base memory, an arithmetic-logic unit, a control unit that can execute non-fuzzy instructions that are typical of conventional microprocessors, and an internal memory for storing the non-fuzzy instructions. The improved fuzzy processor architecture has an ability to load other knowledge bases and other fuzzy rules from outside the processor concurrently and transparently with respect to instruction processing. The processor can also process both fuzzy instructions and non-fuzzy instructions, can perform conditional and unconditional jumps within a set of fuzzy rules that are being processed, and can conditionally swap the knowledge base or the set of rules that are to be processed.

Abstract: A method of data dependence analysis and display of the present invention, from a given program, creates a hierarchical control flow graph containing one of procedure call, basic block, and loop as anode; when a data dependence source or data dependence destination is a procedure call node, loop node, or basic block node, on the hierarchical control flow graph, or a statement analyzes reference regions for a control flow graph for a hierarchy subordinate to the procedure call node or loop node, statements within the basic block, or reference points in the statement; and compares the reference regions to decide the data dependence source and data dependence destination. The above processing is performed on a step-by-step basis, beginning from a specified loop.

Abstract: A cortronic neural network defines connections between neurons in a number of regions using target lists, which identify the output connections of each neuron and the connection strength. Neurons are preferably sparsely interconnected between regions. Training of connection weights employs a three stage process, which involves computation of the contribution to the input intensity of each neuron by every currently active neuron, a competition process that determines the next set of active neurons based on their current input intensity, and a weight adjustment process that updates and normalizes the connection weights based on which neurons won the competition process, and their connectivity with other winning neurons.

Abstract: In a process for designing a fuzzy regulator with at least one input parameter and at least one output parameter (x1, x2, y), where an incomplete rule base with rules that are defined explicitly is supplemented by an implicit rule whose conditional part yields a truth value that has its greatest value when the explicit rules yield a truth value of 0 and is the smallest when the explicit rules have a truth value of 1, the truth value of the implicit rule may be determined by forming the maximum from the truth values of the explicit rules and calculating the complement to 1. This leads to a great simplification of the design of the regulator and prevents instabilities that can occur with an incomplete rule base.

Abstract: In a system of information processing by fuzzy logic, force coefficients are associated with values of variables processed by a fuzzy logic processor. The force coefficients show the degree of urgency with which information sent has to be taken into consideration or indicating the imperative nature of this information. In a network structure, this force coefficient is incorporated into address signals conveyed on the network. Then, in the membership function memories of the fuzzy logic processors, there are memories that take account of the classes of addresses for the extraction therefrom of the character of urgency of the information elements concerned.

Abstract: A fuzzy processor which can be programmed and expanded is disclosed. The fuzzy processor has a membership function I/O circuit for inputting and outputting a plurality of membership functions respectively corresponding to each one of a plurality of features of each one of a plurality of standard patterns. A feature decoder receives a to-be-recognized pattern having a plurality of input features for generating a plurality of feature values. A membership function generator stores the plurality of membership functions and receives the plurality of feature values to generate a plurality of current-type membership degrees for the plurality of input features corresponding to the plurality of standard patterns respectively. A plurality of accumulators receive the plurality of current-type membership degrees respectively for generating a plurality of synthesis membership degrees.

Abstract: In a system of information processing by fuzzy logic, force coefficients are associated with values of variables processed by a fuzzy logic processor. The force coefficients show the degree of urgency with which information sent has to be taken into consideration or indicating the imperative nature of this information. In a network structure, this force coefficient is incorporated into address signals conveyed on the network. Then, in the membership function memories of the fuzzy logic processors, there are memories that take account of the classes of addresses for the extraction therefrom of the character of urgency of the information elements concerned.

Abstract: The present invention relates to the architecture and implementation of real-time knowledge-based fuzzy controller system for general purpose industrial applications. In another aspect the invention relates to the development of an intelligent system which implements fuzzy decision-making procedure which employs selected membership function values such that all signal values present at the input to the fuzzy controller contribute to the controller output at all times thereby simulating dynamical system behavior. In yet another aspect, the invention relates to the development of a fuzzy inference engine which implements an approximate reasoning method based on employing elected membership function values of input signals such that the number of rules which the controller fires is reduced. In this way the fuzzy controller becomes fast and requires less memory than other designs of fuzzy controllers.

Abstract: A processor operating in a fizzy logic's mode and including a fuzzyfication unit receiving a plurality of input variables on its input and being adapted to compute a membership value of such variables in a membership function, a processing unit connected downstream of the fuzzyfication unit to produce a fuzzy set, i.e. the results of fuzzy logic inference operations performed on the plurality of variables, and a defuzzyfication unit operative to translate the inference results into a so-called crisp value. The processor further includes a first memory device connected to the fuzzyfication unit and containing the set of membership functions, a second memory device connected to the defuzzyfication unit and containing the set of crisp value which appear in the THEN part of the fizzy rules, and a further memory device connected to the defuzzyfication unit.

Abstract: In this invention there is disclosed a system and method for generating a fuel-optimal reference velocity profile for a rail-based transportation handling controller. The fuel-optimal reference velocity profile is used to reduce the amount of fuel consumption. The fuel-optimal reference velocity profile is generated to take into account the speed that a train must travel at in order to satisfy a given schedule, speed constraints that will minimize fuel consumption, and recommended speeds that will prevent train breaks, derailments, cargo damage and violation of safety rules. In this invention, the fuel-optimal reference velocity profile is generated by using a genetic algorithm.

Abstract: Fuzzy logic controller for a queue manager that services a plurality of queues in an iterative fashion, each queue containing an indeterminate number of elements, the manager iteratively servicing each of the plurality of queues in accordance with a dequeuing quantity parameter, Q. The controller comprises a device for determining an amount of queues having remaining elements after each servicing iteration and outputting the amount; a device for comparing the difference between a system output representing an amount of queues having remaining elements in a current iteration with a previous output representing an amount of queues having remaining elements in a predecessor iteration, the output difference indicating a first dequeuing trend; and, a device for adjusting the dequeuing quantity parameter Q based on the dequeuing trend, the adjusting device capable of driving the system output toward a predetermined setpoint quantity after each servicing iteration.

Abstract: A current-type fuzzy processor is disclosed. The fuzzy processor comprises a characteristic decoder for decoding a to-be-identified pattern, a plurality of membership function generators for generating a plurality of membership degrees for the to-be-identified pattern, a weighting decoder for generating a weighting value, a plurality of weighting adjustment circuits for performing weighting operations on the plurality of membership degrees according to the weighting value to generate a plurality of weighted membership degrees, a plurality of accumulators for performing accumulation operations on the plurality of weighted membership degrees to generate a plurality of synthesis membership degrees, a WTA circuit for outputting the plurality of synthesis membership degrees in an order of magnitude; and a timing and control logic for generating timing and control signals for the fuzzy processor.

Abstract: An apparatus over or under approximates the result of dividing a binary number representing an integer 2n. The division by 2n is performed by truncating the n least significant bits of the integer. In order to over or under approximate the result, the nth truncated bit, i.e., the most significant bit of the n-truncated less significant bits, is added to the integer represented by the remaining non-truncated bits.

Abstract: The invention relates to a modular architecture of a cellular network for improved large-scale integration, of the type which comprises a plurality of fuzzy cellular elements (C.sub.m,n) interconnected to form a matrix of elements having at least m rows and n columns, the row and column numbers describing the location of each element. Each fuzzy processor is adapted for connection to other processors of the same type such that a parallel architecture of the modular type can be implemented. The management of the architecture is facilitated by each submatrix being controlled by an individually dedicated fuzzy processor device.

Abstract: The present invention relates to a method for controlling thermal processes, whereby measuring devices measure at least two process parameters at least once within a time interval in which a parameter change occurs that is not negligible for the process sequence, the recorded parameters are fed into a control unit, and the control unit regulates the process parameters in the thermal process by means of quantities obtained from the measurements of process parameters.

Abstract: A method and apparatus for controlling tension of a material on a winder by controlling the torque on the winder using a fuzzy logic controller which automatically determines various material and operating characteristics and adjusts torque as a function of the determined characteristics including material density, spindle inertia, material acceleration and diameter of material accumulated on a spindle.

Abstract: An earth moving or construction equipment implement control system is disclosed. The control system includes a fuzzy logic controller that is connected to an electro-hydraulic valve. An implement position sensing system senses the height of the implement. A set point is compared to the implement position to produce an implement position error signal which is an input to the fuzzy logic controller.

Abstract: In a method and arrangement for adapting a sliding mode fuzzy controller to destabilizing changes, control characteristics of the sliding mode fuzzy controller, a closed control loop, are characterized by linguistic variables and are interpreted using linguistic rules in an adaptation block in the control loop which also employs fuzzy control. The rules are configured such that an optimally fast approach of a momentary state condition to the switching line or switching surface of the sliding controller occurs. For adaptation, supporting points are defined in the characteristic of the sliding mode fuzzy controller and these are shifted for the purpose of a desired control behavior, such as by variation of the output fuzzy sets. A separate fuzzy rule set is thus designed for each individual support point.

Abstract: A fuzzy logic algorithm utilizes a single rule to produce a varying output signal. A plurality of input signal values are received from a plurality of sensors. A predetermined combination of a plurality of membership functions in the single fuzzy logic rule are defined in which a first instance of the predetermined combination based on a first set of inputs yields a first output signal defined by a first and second axis. A second instance of the predetermined combination based on a second set of inputs different from the first set of inputs yields a second output signal substantially identical to the first output signal, except the second output signal is shifted along one of the first and second axes. A controller produces digital output signals based on the first and second output signals to produce the varying output signal.

Abstract: A method is provided in which several rules having an identical conditional part and different consequence parts are processed more quickly in that the fuzzification and at least parts of the inference formation are carried out only once, and in which the storage capacity of a knowledge base memory can be reduced, since all identical conditional parts need be stored only once.

Abstract: In a fuzzy control apparatus in which a rule is capable of being changed during operation, a fuzzy reasoning output which prevails immediately prior to a rule change is stored when a rule change is made, and a fuzzy-control output is generated by combining, after the rule change, the stored fuzzy reasoning output which prevailed immediately prior to the rule change and a fuzzy reasoning output which prevails following the rule change. The ratio of the combination is altered in such a manner that, with the passage of time from the moment at which the rule change is made, there is a gradual decrease in a percentage of the fuzzy reasoning output which prevailed immediately prior to the rule change, and a gradual increase in a percentage of the fuzzy reasoning output which prevails following the rule change, in the fuzzy-control output.

Abstract: A fuzzy logic supervisory control architecture for aircraft engines includes a series of fuzzy proportional integral controllers each designed for a specific operating range and a fuzzy logic hierarchical controller for combining the fuel flow derivative outputs of the individual controllers. The hierarchical controller utilizes fuzzy logic on the input space fuzzified to linguistic values for engine temperature, power turbine speed and spool acceleration to determine a weighting to be given to each of the controller outputs for fuel flow derivative.

Abstract: In a fuzzy controller comprising a fuzzy inference device for subjecting one or a plurality of input signals to fuzzy inference operations using membership functions in accordance with a predetermined rule and outputting a non-fuzzy value determined on the basis of the results of the inferences, there are provided an input signal level converter for converting signal levels of the input signals on the input side of the fuzzy inference device and an output signal level converter for converting a signal level of the output signal on the output side of the fuzzy inference device.