Adaptive extended state space predictive control for a kind of nonlinear systems

Area of Science:

• Control Engineering
• Nonlinear System Dynamics
• Adaptive Control Theory

Background:

• Nonlinear systems with output feedback coupling present challenges in control.
• Existing predictive control methods may not fully address system state dynamics.

Purpose of the Study:

• To develop an adaptive nonlinear predictive control strategy for improved system performance.
• To enhance regulatory capacity, robustness, and disturbance rejection in nonlinear systems.

Main Methods:

• Transformation of the nonlinear system into an equivalent time-variant system.
• Design of an extended state space predictive controller incorporating PI optimal regulator structure and P-step setpoint feedforward.
• Inclusion of system state variable changes in the objective function.

Main Results:

• Superior control performance compared to conventional state space predictive control.
• Demonstrated improvements in tracking performance.
• Enhanced robustness and disturbance rejection capabilities.

Conclusions:

• The proposed adaptive nonlinear predictive control strategy offers significant performance improvements.
• The method effectively addresses challenges in nonlinear systems with output feedback coupling.
• This approach provides a robust solution for reference tracking and disturbance rejection.