Patents by Inventor Paul J. Werbos

Paul J. Werbos has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20090299929
    Abstract: Methods, computer-readable media, and systems are provided for machine learning in a simultaneous recurrent neural network. One embodiment of the invention provides a method including initializing one or more weight in the network, initializing parameters of an extended Kalman filter, setting a Jacobian matrix to an empty matrix, augmenting the Jacobian matrix for each of a plurality of training patterns, adjusting the one or more weights using the extended Kalman filter formulas, and calculating a network output for one or more testing patterns.
    Type: Application
    Filed: May 30, 2008
    Publication date: December 3, 2009
    Inventors: Robert Kozma, Paul J. Werbos
  • Publication number: 20090094173
    Abstract: The present invention provides an intelligent power unit, and applications thereof. In an embodiment, the intelligent power unit includes a battery, a power switch, and a control unit. The control unit receives price information and operates the power switch based on the price information to charge the battery during periods of relatively low electrical energy prices. During periods of relatively high electrical energy prices, the control unit cause the energy stored in the battery to be used to power attached loads. The price information provided to the control unit can be actual price information regarding the cost to generate electrical power, estimated price information, or contract price information. It is a feature of the intelligent power unit of the present invention that it can be used to shift a utility's electrical power demand in time.
    Type: Application
    Filed: October 5, 2007
    Publication date: April 9, 2009
    Applicant: Adaptive Logic Control, LLC
    Inventors: Rodney G. SMITH, Ludmilla D. Werbos, Paul J. Werbos
  • Patent number: 6882992
    Abstract: A method and system for implementing a neuro-controller. One example of a neuro-controller is a brain-like stochastic search. Another example is a neuro-controller for controlling a hypersonic aircraft. Using a variety of learning techniques, the method and system provide adaptable control of external devices (e.g., airplanes, plants, factories, and financial systems).
    Type: Grant
    Filed: September 1, 2000
    Date of Patent: April 19, 2005
    Inventor: Paul J. Werbos
  • Patent number: 6708160
    Abstract: A method, system and computer program product for implementing at least one of a learning-based diagnostics system and a control system (e.g., using a neural network). By using ObjectNets to model general object types, it is possible to design a control system that represents system components as relational structures rather than fixed vectors. Such an advance is possible by exploiting non-Euclidean principles of symmetry.
    Type: Grant
    Filed: April 6, 2000
    Date of Patent: March 16, 2004
    Inventor: Paul J. Werbos
  • Patent number: 6581048
    Abstract: A method and system for intelligent control of external devices using a mammalian brain-like structure having three parts. The method and system include a computer-implemented neural network system which is an extension of the model-based adaptive critic design and is applicable to real-time control (e.g., robotic control) and real-time distributed control. Additional uses include data visualization, data mining, and other tasks requiring complex analysis of inter-relationships between data.
    Type: Grant
    Filed: May 10, 1999
    Date of Patent: June 17, 2003
    Inventor: Paul J. Werbos
  • Patent number: 6532454
    Abstract: Classical adaptive control proves total-system stability for control of linear plants, but only for plants meeting very restrictive assumptions. Approximate Dynamic Programming (ADP) has the potential, in principle, to ensure stability without such tight restrictions. It also offers nonlinear and neural extensions for optimal control, with empirically supported links to what is seen in the brain. However, the relevant ADP methods in use today—TD, HDP, DHP, GDHP—and the Galerkin-based versions of these all have serious limitations when used here as parallel distributed real-time learning systems. Either they do not possess quadratic unconditional stability or they lead to incorrect results in the stochastic case. (ADAC or Q-learning designs do not help.) The present invention describes new ADP designs which overcome these limitations.
    Type: Grant
    Filed: September 23, 1999
    Date of Patent: March 11, 2003
    Inventor: Paul J. Werbos
  • Patent number: 6424956
    Abstract: An artificial intelligence system is provided which makes use of a dual subroutine to adapt weights. Elastic Fuzzy Logic (“ELF”) System is provided in which classical neural network learning techniques are combined with fuzzy logic techniques in order to accomplish artificial intelligence tasks such as pattern recognition, expert cloning and trajectory control. The system may be implemented in a computer provided with multiplier means and storage means for storing a vector of weights to be used as multiplier factors in an apparatus for fuzzy control.
    Type: Grant
    Filed: March 18, 1999
    Date of Patent: July 23, 2002
    Inventor: Paul J. Werbos
  • Patent number: 6169981
    Abstract: A method and system for intelligent control of external devices using a mammalian brain-like structure having three parts. The method and system include a computer-implemented neural network system which is an extension of the model-based adaptive critic design and is applicable to real-time control (e.g., robotic control) and real-time distributed control. Additional uses include data visualization, data mining, and other tasks requiring complex analysis of inter-relationships between data.
    Type: Grant
    Filed: June 4, 1997
    Date of Patent: January 2, 2001
    Inventor: Paul J. Werbos
  • Patent number: 5924085
    Abstract: An artificial intelligence system is provided which makes use of a dual subroutine to adapt weights. Elastic Fuzzy Logic ("ELF") System is provided in which classical neural network learning techniques are combined with fuzzy logic techniques in order to accomplish artificial intelligence tasks such as pattern recognition, expert cloning and trajectory control. The system may be implemented in a computer provided with multiplier means and storage means for storing a vector of weights to be used as multiplier factors in an apparatus for fuzzy control.
    Type: Grant
    Filed: May 23, 1997
    Date of Patent: July 13, 1999
    Inventor: Paul J. Werbos
  • Patent number: 5751915
    Abstract: An artificial intelligence system is provided which makes use of a dual subroutine to adapt weights. Elastic Fuzzy Logic ("ELF") System is provided in which classical neural network learning techniques are combined with fuzzy logic techniques in order to accomplish artificial intelligence tasks such as pattern recognition, expert cloning and trajectory control. The system may be implemented in a computer provided with multiplier means and storage means for storing a vector of weights to be used as multiplier factors in an apparatus for fuzzy control.
    Type: Grant
    Filed: August 31, 1993
    Date of Patent: May 12, 1998
    Inventor: Paul J. Werbos