초록 ▼

A neural network is trained with a general set of data to function as a general model of a machine or process with local condition inputs set equal to zero. The network is then retrained or receives additional training on an extentd data set containing the general set of data, characterized by zero

A neural network is trained with a general set of data to function as a general model of a machine or process with local condition inputs set equal to zero. The network is then retrained or receives additional training on an extentd data set containing the general set of data, characterized by zero values for the local condition inputs, and data on specific local conditions, characterized by non-zero values for the local condition inputs. The result is a trained neural network which functions as a general model when the inputs for the local conditions inputs are set equal to zero, and which functions as a model of some specific local condition when the local condition inputs match the encoding of the some local data set contained within the training data. The neural network has an architecture and a number of neurons such that its functioning as the local model is partially dependent upon its functioning as the general model. This trained neural network is combined with sensors, actuators, a control and communications computer and with a user interface to function as combine control system.

대표청구항 ▼

A machine control system for controlling a machine which operates in a variety of locations and conditions and which produces an end result, the control system comprising: a plurality of actuators, each for controlling a particular function of the machine in response to an actuator control signal; a

A machine control system for controlling a machine which operates in a variety of locations and conditions and which produces an end result, the control system comprising: a plurality of actuators, each for controlling a particular function of the machine in response to an actuator control signal; a plurality of actuator sensors, each generating an actuator condition signal representing a condition of a corresponding one of the actuators; a plurality of input condition sensors, each generating an input condition sensor signal representing an input condition which influences operation of the machine, an actuator control unit for generating the actuator control signals as a function of the actuator condition signals and as a function of setpoint signals; a neural network trained prior to and apart from normal production use of the machine with a set of general training data to function as a general model of the machine and trained to function as a submodel with respect to a set of local condition data together with the set of general training data, the neural network processing the input condition sensor signals and data collected prior to normal production use of the machine representing desired machine performance quality to produce a set of machine adjustments intended to produce the desired machine performance quality, the neural network generating the setpoint signals based upon predicted responses of the machine to varying conditions; a data communication system comprising means for communicating the actuator signals to the actuator control unit, means for communicating the sensor signals to the neural network, and means for communicating the setpoint signals to the actuator control unit, the neural network and the actuator control unit cooperating to control operation of the machine without measuring the machine performance quality in connection with normal production use of the machine; and operator controlled means for selectively causing the neural network to function as the general model or as the submodel.