An instrumental variable algorithm is presented that estimates the coefficients of a continuous transfer function model directly from sampled data. The algorithm is based on instrumental variables extracted from an auxiliary model and input and output signal derivatives estimated by filtered difference equations. As a result, this method does not require any prior knowledge of the output noise. To ensure the validity of the filtered derivative estimates, a criterion based on the Nyquist frequency and the system bandwidth is established. Then the concept of asymptotic consistency is applied to the proposed instrumental variable algorithm to identify the conditions for convergence of the model parameter estimates. Specifically, the asymptotic consistency conditions impose a continuous and persistent exciting constraint on the input signal. This is analogous to the persistent excitation condition for identification of discrete models. The proposed instrumental variable algorithm is demonstrated within an auto-tuning algorithm for feedback controllers based on plant inversion. In this application, the algorithm is only suitable for lower-order transfer functions that are minimum-phase and stable. These types of systems are common in industrial applications for manufacturing and process control. Here, the algorithm is experimentally validated for automatic tuning of the idle speed controller on a 4.6L Ford V-8 spark ignition engine.
Skip Nav Destination
e-mail: pjcunnin@purdue.edu
Article navigation
March 2007
Technical Papers
An Instrumental Variable Method for Continuous-Time Transfer Function Model Identification With Application to Controller Auto-Tuning
Patrick J. Cunningham,
Patrick J. Cunningham
Ray W. Herrick Laboratories,
e-mail: pjcunnin@purdue.edu
Purdue University
, 140 South Intramural Drive, West Lafayette, IN 47907-2031
Search for other works by this author on:
Matthew A. Franchek
Matthew A. Franchek
Search for other works by this author on:
Patrick J. Cunningham
Ray W. Herrick Laboratories,
Purdue University
, 140 South Intramural Drive, West Lafayette, IN 47907-2031e-mail: pjcunnin@purdue.edu
Matthew A. Franchek
J. Dyn. Sys., Meas., Control. Mar 2007, 129(2): 154-162 (9 pages)
Published Online: July 14, 2006
Article history
Received:
November 15, 2004
Revised:
July 14, 2006
Citation
Cunningham, P. J., and Franchek, M. A. (July 14, 2006). "An Instrumental Variable Method for Continuous-Time Transfer Function Model Identification With Application to Controller Auto-Tuning." ASME. J. Dyn. Sys., Meas., Control. March 2007; 129(2): 154–162. https://doi.org/10.1115/1.2432359
Download citation file:
Get Email Alerts
Cited By
Offline and Online Exergy-Based Strategies for Hybrid Electric Vehicles
J. Dyn. Sys., Meas., Control (May 2025)
Multi Combustor Turbine Engine Acceleration Process Control Law Design
J. Dyn. Sys., Meas., Control
A Distributed Layered Planning and Control Algorithm for Teams of Quadrupedal Robots: An Obstacle-Aware Nonlinear Model Predictive Control Approach
J. Dyn. Sys., Meas., Control (May 2025)
Active Data-Enabled Robot Learning of Elastic Workpiece Interactions
J. Dyn. Sys., Meas., Control (May 2025)
Related Articles
Autonomous Vibration Suppression Using On-Line Pole-Zero Identification
J. Vib. Acoust (October,2001)
Stabilizing PID Controllers for a Single-Link Biomechanical Model with Position, Velocity, and Force Feedback
J Biomech Eng (December,2004)
On Multiloop Interaction and Relative and Bristol
Gains
J. Dyn. Sys., Meas., Control (December,2006)
Control of Flexible Structures Governed by the Wave Equation Using Infinite Dimensional Transfer Functions
J. Dyn. Sys., Meas., Control (December,2005)
Related Proceedings Papers
Related Chapters
Graphical Methods for Control Systems
Introduction to Dynamics and Control in Mechanical Engineering Systems
Mash 2-1 Multi-Bit Sigma-Delta Modulator for WLAN
International Conference on Future Computer and Communication, 3rd (ICFCC 2011)
QP Based Encoder Feedback Control
Robot Manipulator Redundancy Resolution