Adaptive event-triggered tracking control for strict-feedback nonlinear ODE cascaded n+1 coupled hyperbolic PDE...

Area of Science:

• Control Systems Engineering
• Applied Mathematics
• Robotics

Background:

• Addresses challenges in controlling cascaded nonlinear ordinary differential equation (ODE) and hyperbolic partial differential equation (PDE) systems.
• Focuses on systems with uncertainty and strict-feedback configurations, common in applications like crane systems.
• Highlights limitations of existing time-triggered stabilization control for such complex systems.

Purpose of the Study:

• Develop adaptive event-triggered tracking control for a specific class of ODE-PDE systems.
• Overcome difficulties in checking input-to-state stability for nonlinear, uncertain cascaded systems.
• Solve the open problem of boundary event-triggered tracking control for these systems.

Main Methods:

• Combines geometric design methods with infinite- and finite-dimensional backstepping techniques.
• Designs an adaptive tracking controller for the nonlinear ODE-PDE system.
• Proposes a dynamic event-triggered mechanism to minimize control actuation frequency.

Main Results:

• Successfully constructed an adaptive tracking controller for the challenging system.
• Developed a dynamic event-triggered mechanism that reduces control update frequency.
• Provided rigorous theoretical proof of asymptotic convergence for tracking errors and minimal dwell-time.

Conclusions:

• The proposed adaptive event-triggered control scheme effectively manages complex ODE-PDE systems.
• The dynamic event-triggered mechanism enhances control efficiency by reducing actuation.
• Validated through simulations on a crane system, demonstrating practical applicability and effectiveness.