17868268. VIBRATION ACTUATOR CONTROL APPARATUS, VIBRATION DRIVING APPARATUS, INTERCHANGEABLE LENS, IMAGING APPARATUS, AND AUTOMATIC STAGE simplified abstract (CANON KABUSHIKI KAISHA)

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VIBRATION ACTUATOR CONTROL APPARATUS, VIBRATION DRIVING APPARATUS, INTERCHANGEABLE LENS, IMAGING APPARATUS, AND AUTOMATIC STAGE

Organization Name

CANON KABUSHIKI KAISHA

Inventor(s)

Jun Sumioka of Kanagawa (JP)

VIBRATION ACTUATOR CONTROL APPARATUS, VIBRATION DRIVING APPARATUS, INTERCHANGEABLE LENS, IMAGING APPARATUS, AND AUTOMATIC STAGE - A simplified explanation of the abstract

This abstract first appeared for US patent application 17868268 titled 'VIBRATION ACTUATOR CONTROL APPARATUS, VIBRATION DRIVING APPARATUS, INTERCHANGEABLE LENS, IMAGING APPARATUS, AND AUTOMATIC STAGE

Simplified Explanation

The patent application describes a control apparatus for a vibration actuator that uses machine learning to output a control amount. This control amount is used to move a contact body relative to the vibrator.

  • The control apparatus includes a trained model that is trained using machine learning techniques.
  • The trained model takes inputs such as the target speed and a value based on the target position, and outputs a control amount.
  • The value based on the target position is calculated using a product of two values.
  • The first value is based on the difference between the target position and a detection position that is obtained from the vibration actuator.
  • The second value is based on the ratio between the control amount output from the control apparatus and a value obtained from the trained model when the target speed and a predetermined value are input.

Potential applications of this technology:

  • Control of vibration actuators in various devices such as smartphones, gaming controllers, and wearable devices.
  • Haptic feedback systems in virtual reality or augmented reality applications.
  • Precision control of robotic systems that require precise movement and positioning.

Problems solved by this technology:

  • Traditional control methods for vibration actuators may not provide precise and efficient control.
  • Machine learning techniques can improve the control accuracy and responsiveness of vibration actuators.
  • The trained model can adapt to different operating conditions and optimize the control output.

Benefits of this technology:

  • Improved control accuracy and responsiveness of vibration actuators.
  • Adaptability to different operating conditions and optimization of control output.
  • Potential for energy efficiency by optimizing the control amount output.


Original Abstract Submitted

A vibration actuator control apparatus includes a control amount output unit. The control amount output unit includes a trained model trained by machine learning configured to output a control amount, if the target speed and a value based on the target position are input to the trained model, to move the contact body relative to the vibrator. The value based on the target position is a value based on a product of first and second values. The first value is a value based on a difference between the target position and a detection position detected from the vibration actuator moved based on the control amount. The second value is a value based on a ratio between the control amount output from the control amount output unit and a value output from the trained model if the target speed and a predetermined value are input to the trained model.