Optimal infinite horizon control under a low data rate
System Identification, Volume # 14 | Part# 1
Authors
Girish N. Nair; Minyi Huang; Robin J. Evans
Identifier
10.3182/20060329-3-AU-2901.00179
Index Terms
optimal control,communication channels,quantization
Abstract
This paper considers the optimal control of linear systems where measurement data is transmitted from the plant output to the controller over a noiseless communication channel with limited instantaneous data rate. The cost is defined to be the average, over a random initial state, of the usual infinite horizon quadratic regulation criterion, and the number of bits transported by the channel during each sampling interval is bounded. Several fundamental properties of the optimal cost functional are derived for initial state densities that satisfy a mild moment condition. Using these properties, precise expressions for the optimal cost and policy are obtained assuming a uniformly distributed initial state. These expressions agree with the classical optimal LQR results in the high data rate limit and with recent minimum rate results in the low rate regime. Extensions to the case of non-uniform densities and vector-valued states are discussed.
References
[1] Baillieul, J. (2001). Feedback designs
in information-based control. In: Stochastic
Theory and Control Proceedings of a Workshop
held in Lawrence, Kansas (B. Pasik-Duncan,
Ed.), Springer. pp. 35-57.
[2] Brockett, R. W. and D. Liberzon (2000). Quantized
feedback stabilization of linear systems.
IEEE Trans. Autom. Contr. 45(7), 1279-89.
[3] Delchamps, D. F. (1990). Stabilizing a linear system
with quantized state feedback. IEEE
Trans. Autom. Contr. 35, 916-24.
[4] Fagnani, F. and S. Zampieri (2003). Stability analysis
and synthesis for scalar linear systems
with a quantized feedback. IEEE Trans. Autom.
Contr. 48(9), 1569-84.
[5] Fagnani, F. and S. Zampieri (2004a). Quantized
stabilization of linear systems: complexity
versus performance. IEEE Trans. Autom.
Contr. 49(9), 1534-48.
[6] Fagnani, F. and S. Zampieri (2004b). Tree structured
vector quantization and quantized control.
Preprint.
[7] Gersho, A. and R. M. Gray (1993). Vector Quantization
and Signal Compression. Kluwer.
[8] Ishii, H. and B. A. Francis (2003). Quadratic
stabilization of sampled-data systems with
quantization. Automatica 39(10), 1793-1800.
[9] Li, K. and J. Baillieul (2004). Robust quantization
for digital finite communication bandwidth
(dfcb) control. IEEE Trans. Autom. Contr.
49(9), 1573-97.
[10] Liberzon, D. (2003). On stabilization of linear
systems with limited information. IEEE
Trans. Autom. Contr. 48(2), 304-7.
[11] Nair, G. N. and R. J. Evans (2000). Stabilization
with data-rate-limited feedback: tightest attainable
bounds. Sys. Contr. Lett. 41(1), 49-
56.
[12] Nair, G. N. and R. J. Evans (2003). Exponential
stabilisability of finite-dimensional linear
systems with limited data rates. Automatica
39, 585-93.
[13] Nair, G. N. and R. J. Evans (2004). Stabilizability
of stochastic linear systems with finite
feedback data rates. SIAM Jour. Contr. Optim.
43(2), 413-36. Short version published
in Proc. 41st IEEE Conf. Dec. Contr., 2002.
[14] Petersen, I. R. and A. V. Savkin (2001). Multi-rate
stabilization of multivariable discrete-time
linear systems via a limited capacity
communication channel. In: Proc. 40th IEEE
Conf. Dec. Contr., pp. 304-9.
[15] Special Issue on Networked Control Systems
(2004). IEEE Trans. Autom. Contr.
[16] Tatikonda, S., A. Sahai and S. Mitter (2004).
Stochastic linear control over a communication
channel. IEEE Trans. Autom. Contr.
49(9), 1549-61.
[17] Tatikonda, S. and S. Mitter (2000). Control under
communication constraints. In: Proc. 38th
Ann. Allerton Conf. Comm. Contr. Comp.,
pp. 182-90.
[18] Wong, W. S. and R. W. Brockett (1999). Systems
with finite communication bandwidth
constraints II: stabilization with limited information
feedback. IEEE Trans. Autom. Contr.
44, 1049-53.
[19] Yuksel, S., O. C. Imer and T. Basar (2004).
Constrained state estimation and control
over communication networks. In: Proc. 38th
Ann. Conf. Inf. Sci. Syst..
