Improved Dynamic Event-Triggered Robust Control for Flexible Robotic Arm Systems with Semi-Markov Jump Process

Area of Science:

• Robotics
• Control Systems Engineering
• Stochastic Systems

Background:

• Flexible robotic arms require robust control for stability, especially with changing inertia.
• Specialized robots (surgical, assisted-living) have strict lightweight needs and operate in dynamic environments.
• Networked control systems face bandwidth limitations and security threats like DoS attacks.

Purpose of the Study:

• To design a dynamic event-triggered robust controller for flexible robotic arm systems.
• To model system uncertainties using a continuous-time phase-type semi-Markov jump process.
• To ensure secure and stable control under varying inertia, network constraints, and DoS attacks.

Main Methods:

• A semi-Markov chain models the system's dynamic behavior.
• A dynamic event-triggered scheme addresses network bandwidth limitations and DoS attacks.
• Lyapunov function approach derives criteria for resilient H∞ controller existence.

Main Results:

• Co-design of controller gains, Lyapunov parameters, and event-triggered parameters.
• Adequate criteria for the resilient H∞ controller are established.
• Controller effectiveness validated through numerical simulations using MATLAB's LMI toolbox.

Conclusions:

• The proposed dynamic event-triggered robust controller effectively enhances stability and security for flexible robotic arms.
• The methodology addresses critical challenges including changing inertia and network vulnerabilities.
• This research contributes to safer and more reliable operation of specialized robotic systems.