ADP-Based Event-Triggered Constrained Optimal Control on Spatiotemporal Process: Application to Temperature Field in...

Area of Science:

• Materials Science
• Chemical Engineering
• Control Systems Engineering

Background:

• Precise temperature control in roller kilns is vital for producing Ni-Co-Mn layered cathode materials for lithium-ion batteries.
• The production process is highly sensitive to temperature distribution, necessitating advanced control strategies.

Purpose of the Study:

• To propose an event-triggered optimal control (ETOC) method for managing the temperature field in roller kilns.
• To reduce communication and computation costs associated with traditional control methods.
• To ensure the stability and performance of the temperature control system under input constraints.

Main Methods:

• Developed an event-triggered optimal control (ETOC) method using a nonquadratic cost function to account for input constraints.
• Modeled the temperature field using a partial differential equation (PDE).
• Proposed an event-triggered adaptive dynamic programming (ETADP) framework incorporating model reduction, a critic neural network (NN), and an actor network.

Main Results:

• The ETOC method effectively controls the temperature field, reducing communication and computation overhead.
• The ETADP framework, based on model reduction, optimizes control strategies and performance indices.
• Stability of the closed-loop PDE system and performance bounds were theoretically proven.

Conclusions:

• The proposed event-triggered optimal control method is effective for precise temperature field management in roller kiln production.
• The ETADP framework offers a computationally efficient and stable approach for complex PDE systems.
• This research contributes to improved manufacturing processes for advanced battery materials.