Adaptive dead-time compensation with application to a robotic welding system

The paper proposes a paradigm for control design suitable for poorly modeled plants with significant dead-time. An adaptive dead-time compensator is developed which is substantially different to the standard Smith predictor, and more generally applicable in practice. A framework is developed for selecting the controller parameters using now standard design techniques such as /spl mu/-synthesis. It is argued that adaptation allows for exact set point matching without the need for integration in the control law. Stability and convergence results are established for the resulting closed-loop system equations. The proposed adaptive dead-time compensator is compared with both a standard robust controller and an adaptive pole placement controller through experiments on a gas metal arc welding testbed.

[1]  R. Stout,et al.  Weldability of steels , 1971 .

[2]  Pravin Varaiya,et al.  Stochastic Systems: Estimation, Identification, and Adaptive Control , 1986 .

[3]  K. S. Smith,et al.  Time domain simulation of cycloconverter-fed variable speed AC drives with closed-loop control , 1994 .

[4]  T. Lai,et al.  Least Squares Estimates in Stochastic Regression Models with Applications to Identification and Control of Dynamic Systems , 1982 .

[5]  Eliahu Ibrahim Jury,et al.  Sampled-data control systems , 1977 .

[6]  Sean P. Meyn,et al.  Adaptive dead time compensation , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[7]  Sean P. Meyn,et al.  A synthesis of classical and adaptive control , 1993, Proceedings of IEEE International Conference on Control and Applications.

[8]  G. Wittum,et al.  Adaptive filtering , 1997 .

[9]  R. Baheti.  Vision processing and control of robotic Arc welding system , 1985, 1985 24th IEEE Conference on Decision and Control.

[10]  Sean P. Meyn,et al.  Prediction and adaptation in PID controller design , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[11]  Zalman J. Palmor,et al.  Stability properties of Smith dead-time compensator controllers , 1980 .

[12]  Mohammed M'Saad,et al.  Robust adaptive regulation with minimal prior knowledge , 1992 .

[13]  Han-Fu Chen,et al.  Convergence rate of least-squares identification and adaptive control for stochastic systems† , 1986 .

[14]  H. Raynaud,et al.  A robust solution to the admissibility problem in indirect adaptive control without persistency of excitation , 1988 .

[15]  Graham C. Goodwin,et al.  Adaptive filtering prediction and control , 1984 .

[16]  Lei Guo.  Estimating time-varying parameters by the Kalman filter based algorithm: stability and convergence , 1990 .

[17]  O Smith,et al.  CLOSER CONTROL OF LOOPS WITH DEAD TIME , 1957 .

[18]  P. V. Kokotovic,et al.  Adaptive Control of an Arc Welding Process , 1991, 1991 American Control Conference.

[19]  D.V. Nishar,et al.  Adaptive control of temperature in arc welding , 1994, IEEE Control Systems.

[20]  D. V. Nishar,et al.  Adaptive control of temperature in arc welding , 1994 .

[21]  R.R. Bitmead,et al.  A self-tuning regulator for vibration control , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[22]  T. Lai,et al.  Extended least squares and their applications to adaptive control and prediction in linear systems , 1986 .

[23]  Karl Johan Åström,et al.  Frequency domain properties of Otto Smith regulators , 1977 .

[24]  D. Mayne,et al.  Design issues in adaptive control , 1988 .

[25]  Sean P. Meyn,et al.  Model reference adaptive control of time varying and stochastic systems , 1993, IEEE Trans. Autom. Control..

[26]  K. Poolla,et al.  Uniformly optimal control of linear time-invariant plants: Nonlinear time-varying controllers , 1986 .

[27]  J. R. Ragazzini,et al.  Sampled-Data Control Systems , 1959 .

[28]  Sigurd Skogestad,et al.  Robust control of time-delay systems using the Smith predictor , 1993 .

[29]  D. Mayne,et al.  Continuous-time stochastic model reference adaptive control , 1991 .

[30]  W. Ren,et al.  Stochastic adaptive system theory : recent advances and a reappraisal , 1991 .