Input nonlinearities, or actuator nonlinearities, can be seen in a lot of systems and have significant effects on the system performance. From the controller design point of view, accurate yet simple model of input nonlinearities is essential to compensate their effects and to achieve high level control performance. Unfortunately, most input nonlinearities are neither known nor easy to characterize, especially when the input nonlinearities and unknown system parameters are present simultaneously in the system dynamics. Off-board calibration may be possible yet it is very time consuming and requires additional calibration systems. This paper focuses on a class of systems with unknown input nonlinearities and system parameters and proposes an on-board system identification process to model the unknown nonlinearities. The input nonlinearities are decomposed into localized orthogonal basis and then estimated together with the system parameters. The proposed method is applied to model the nonlinear flow mapping of cartridge valves. Simulation and experimental results are obtained to illustrate the effectiveness and practicality of the proposed method.

Volume Subject Area:
Dynamic Systems and Technology
Topics:
Actuators, Calibration, Control equipment, Design, Flow (Dynamics), Simulation, System dynamics, Valves
1.
Tao, G., and Kokotovic, P. V., 1996. Adaptive Control of Systems with Actuator and Sensor Nonlinearities. John Wiley & Sons, Inc.
2.
Liu, S., and Yao, B., 2004. “Characterization and attenuation of sandwiched deadband problem using describing function analysis and its application to electro-hydraulic systems controlled by closed-center valves.” In ASME International Mechanical Engineering Congree and Exposition. IMECE 2004-60946.
3.
Fortgang, J. D., George, L. E., and Book, W. J., 2002. “Practical implementation of a dead zone inverse on a hydraulic wrist.” In Proc. of ASME International Mechanical Engineering Congress and Exposition. IMECE 2002-39351.
4.
Bu, F., and Yao, B., 2000. “Nonlinear adaptive robust control of hydraulic actuators regulated by proportional directional control valves with deadband and nonlinear flow gain coefficients.” In Proc. of American Control Conference, pp. 4129–4133.
5.
Taware, A., Tao, G., and Teolis, C., 2001. “An adaptive dead-zone inverse controller for systems with sandwiched dead-zones.” In Proceedings of the American Control Conference, pp. 2456–2461.
6.
Haykin, S., 1999. Neural Networks, A Comprehensive Foundation, 2nd ed. Pearson Education.
7.
Oppenheim, A. V., and Schafer, R.W., 1985. Digital Signal Processing. Prentice Hall, N.J.
8.
Mallat, S., 1999. A Wavelet Tour of Signal Processing. Academic Press.
9.
Karl J. A`stro¨m and Bjo¨rn Wittenmark, 1995. Adaptive Control, 2nd edition ed. Addison-Wesley.
10.
Merritt, H. E., 1967. Hydraulic Control Systems. John Wiley & Sons.
11.
Liu, S., and Yao, B., 2003. “Coordinate control of energysaving programmable valves.” In ASME International Mechanical Engineering Congress and Exposition. IMECE 2003-42668.
12.
Liu, S., and Yao, B., 2004. “Programmable valves: a solution to bypass deadband problem of electro-hydraulic systems.” In Proc. of American Control Conference, pp. 4438–4443.
13.
Liu, S., and Yao, B., 2004. “Adaptive robust control of programmable valves with manufacture supplied flow mapping only.” In IEEE Conference on Decision and Control.
This content is only available via PDF.
Copyright © 2005
 by ASME
You do not currently have access to this content.