Patents by Inventor Kent E. Heckendoorn

Kent E. Heckendoorn 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).

  • Control system using an adaptive neural network for target and path optimization for a multivariable, nonlinear process
    Patent number: 5640491
    Abstract: A control system having four major components: a target optimizer, a path optimizer, a neural network adaptation controller and a neural network. In the target optimizer, the controlled variables are optimized to provide the most economically desirable outputs, subject to operating constraints. Various manipulated variable and disturbance values are provided for modeling purposes. The neural network receives as inputs a plurality of settings for each manipulated and disturbance variable. For target optimization all the neural network input values are set equal to produce a steady state controlled variable value. The entire process is repeated with differing manipulated variable values until an optimal solution develops. The resulting target controlled and manipulated variable values are provided to the path optimizer to allow the manipulated variables to be adjusted to obtain the target output. Various manipulated variable values are developed to model moves from current to desired values.
    Type: Grant
    Filed: December 18, 1995
    Date of Patent: June 17, 1997
    Assignees: Texaco, Inc., Neuralware, Inc.
    Inventors: Naveen V. Bhat, William B. Braden, Kent E. Heckendoorn, Timothy J. Graettinger, Alexander J. Federowicz, Paul A. Dubose
  • Control system using an adaptive neural network for target and path optimization for a multivariable, nonlinear process
    Patent number: 5477444
    Abstract: A control system having four major components: a target optimizer, a path optimizer, a neural network adaptation controller and a neural network. In the target optimizer, the controlled variables are optimized to provide the most economically desirable outputs, subject to operating constraints. Various manipulated variable and disturbance values are provided for modeling purposes. The neural network receives as inputs a plurality of settings for each manipulated and disturbance variable. For target optimization all the neural network input values are set equal to produce a steady state controlled variable value. The entire process is repeated with differing manipulated variable values until an optimal solution develops. The resulting target controlled and manipulated variable values are provided to the path optimizer to allow the manipulated variables to be adjusted to obtain the target output. Various manipulated variable values are developed to model moves from current to desired values.
    Type: Grant
    Filed: September 14, 1992
    Date of Patent: December 19, 1995
    Inventors: Naveen V. Bhat, William B. Braden, Kent E. Heckendoorn, Timothy J. Graettinger, Alexander J. Federowicz, Paul A. DuBose