On-line identification of cascade control systems based on half limit cycle data

Area of Science:

• Control Systems Engineering
• Process Identification
• Automation Technology

Background:

• Cascade control systems are widely used in industrial processes.
• Accurate process models are crucial for effective controller tuning.
• Conventional identification methods can be time-consuming and disruptive.

Purpose of the Study:

• To develop an on-line identification procedure for cascade control systems.
• To model inner and outer loop process dynamics simultaneously.
• To avoid breaking the closed-loop control during identification.

Main Methods:

• A novel on-line identification procedure is proposed.
• The method models both inner and outer loop dynamics concurrently.
• It utilizes limit cycle data from a single experiment without controller replacement.

Main Results:

• Exact analytical expressions for process model parameters were derived.
• The procedure was validated through simulation examples.
• The effectiveness of the proposed method was demonstrated.

Conclusions:

• The presented on-line identification procedure offers an efficient way to model cascade control systems.
• It successfully identifies process dynamics without interrupting closed-loop operation.
• This method provides a valuable tool for real-time control system optimization.