Further Results on Optimal Tracking Control for Nonlinear Systems With Nonzero Equilibrium via Adaptive Dynamic...

Area of Science:

• Control Engineering
• Artificial Intelligence
• Nonlinear System Dynamics

Background:

• Traditional optimal control problems often require systems to have a zero equilibrium for finite cost functions and unique solutions.
• Solving optimal tracking control for nonlinear systems with nonzero equilibrium presents significant challenges.

Purpose of the Study:

• To develop a novel cost function to address limitations in optimal tracking control for nonlinear systems.
• To enable the application of adaptive dynamic programming (ADP) to nonlinear systems with nonzero equilibrium.

Main Methods:

• A new performance index function is designed, specifically tailored for tracking errors and their derivatives.
• This novel cost function removes the necessity for a zero equilibrium assumption.
• The adaptive dynamic programming (ADP) technique is employed for controller design.

Main Results:

• The proposed cost function simplifies the controller design process for nonlinear systems.
• Effectiveness is demonstrated through comparative simulations on an inverted pendulum system.
• The new strategy overcomes obstacles associated with nonzero equilibrium in optimal tracking control.

Conclusions:

• The developed cost function effectively solves the optimal tracking control problem for nonlinear systems with nonzero equilibrium.
• The proposed method offers a simplified and advantageous approach compared to traditional techniques.
• This research advances the application of adaptive dynamic programming in complex control scenarios.