Adaptive control system for automated vehicle applications

A vehicle comprising:

• an automated device that is actuated by a motor;
• a motor sensor having a motor sensor output signal that is related to an output characteristic of the motor;
• a position sensor having a position sensor output signal that is related to a position of the automated device;
• and
• a feedback control module comprising:
• an adaptive logic module comprising a neural network configured with a calibrated kinematic model of an operating behavior of the automated device and further configured to recognize deviations in the calibrated operating behavior pattern of the automated closure device based on the motor sensor output signal and the position sensor output signal and configured to determine when the automated device is obstructed by an obstacle based on the deviations;
• and
• a command module communicatively coupled to the adaptive logic module and configured to generate a control signal to drive the motor based on a comparison of the motor sensor output signal and the position sensor signal to a stored operating behavior pattern from the kinematic model of the automated device.

A method of controlling an automated device in a vehicle via neural network, wherein the automated device is actuated by a motor, the method comprising:

• receiving input data by the neural network related to a load on the motor and to a position of the automated device;
• processing the input data by identifying frequency patterns in the input data;
• comparing the input data patterns to a kinematic data model of an operating behavior of the automated device;
• determining if the automated device is obstructed by an obstacle based on identifying deviations from the kinematic data model of the operating behavior by the patterns in the input data;
• and
• driving the motor based upon the determination of whether the automated device is obstructed.