Real-Time H_∞ Control of Networked Inverted Pendulum Visual Servo Systems.

Area of Science:

• Robotics and Control Systems
• Networked Control Systems
• Computational Vision

Background:

• Networked visual servo control systems often neglect simultaneous consideration of network communication duration and image processing computational costs.
• Existing methods frequently overlook computational expenses in measurement, actuation, and control processes.
• Networked inverted pendulum systems face challenges from time-varying delays and computational errors.

Purpose of the Study:

• To propose a novel platform for networked inverted pendulum visual servo control that integrates H∞ analysis.
• To address the simultaneous challenges of network communication duration and image processing computational cost.
• To develop a robust control strategy for systems with multiple time-varying delays and computational errors.

Main Methods:

• Design of a novel event-triggered sampling mechanism.
• Application of a new closed-loop strategy for networked inverted pendulum visual servo systems.
• Utilization of Lyapunov stability theory to prove system stability.
• Implementation of an H∞ controller for disturbance attenuation, evaluating computational errors using the H∞ disturbance attenuation level γ.

Main Results:

• The proposed system achieves stability despite compromising image-induced computational and network-induced delays and system performance.
• The H∞ controller effectively evaluates and manages computational errors.
• Simulation and experimental results validate the system's performance.

Conclusions:

• The developed platform successfully reduces computational errors in networked inverted pendulum visual servo control.
• The system maintains efficiency and robustness in the presence of network and computational challenges.
• The integration of H∞ analysis provides a robust framework for networked control systems.