Practical Prescribed Time Control of Euler-Lagrange Systems With Partial/Full State Constraints: A Settling Time...

Area of Science:

• Engineering
• Control Theory
• Robotics

Background:

• Euler-Lagrange (EL) systems are fundamental in many engineering applications, including robotics and mechanical systems.
• Designing controllers for EL systems with state constraints and precise timing requirements is challenging.

Purpose of the Study:

• To develop a practical prescribed-time tracking control scheme for Euler-Lagrange (EL) systems.
• To address control design under partial or full state constraints.
• To achieve user-defined tracking precision within a predetermined settling time.

Main Methods:

• Introduction of a settling time regulator to create a novel performance function.
• Development of a new neural adaptive control scheme.
• Utilizing system transformation techniques to convert state constraint problems into boundedness of new variables.

Main Results:

• The proposed control scheme achieves prescribed-time tracking precision for EL systems.
• State constraints (partial or full) are effectively managed without altering the control structure.
• Both settling time and tracking precision are controllable parameters.

Conclusions:

• The developed neural adaptive control offers a flexible and effective solution for EL systems with state constraints.
• The method successfully guarantees tracking precision within a prescribed time, enhancing practical applicability.
• Simulation results validate the effectiveness and robustness of the proposed control strategy.