Identification of FOPDT and SOPDT process dynamics using closed loop test

Area of Science:

• Control Engineering
• Process Identification
• System Dynamics

Background:

• Accurate process model identification is crucial for effective control system design.
• Existing methods often struggle with measurement noise and time delays in real-time systems.
• Characterizing both stable and unstable dynamics, including second-order systems, remains a challenge.

Purpose of the Study:

• To develop a robust method for identifying process dynamics, including stable/unstable and time-delayed systems.
• To estimate unknown process model parameters using a limit cycle generated by a relay with hysteresis.
• To address the impact of measurement noise on process identification.

Main Methods:

• Utilizing a relay with hysteresis to induce a limit cycle output for parameter estimation.
• Deriving state-space based generalized analytical expressions for accurate model identification.
• Developing a multiloop control strategy to mitigate measurement noise and recover the limit cycle.

Main Results:

• Accurate identification of first-order and second-order (overdamped/underdamped) process dynamics with time delay.
• Demonstrated robustness against measurement noise through the use of hysteresis and a novel control strategy.
• Validated effectiveness for systems with and without zeros via simulation.

Conclusions:

• The proposed relay-based identification method provides accurate and noise-resilient estimation of process dynamics.
• The developed analytical expressions and control strategy offer a significant improvement for real-time system identification.
• This technique is effective for a wide range of process models, including those with time delays and zeros.