An Augmented Automatic Choosing Control with Constrained Input Using Weighted Gradient Optimization Automatic Choosing Functions

In this paper we consider a nonlinear feedback control
called augmented automatic choosing control (AACC) for nonlinear
systems with constrained input using weighted gradient optimization
automatic choosing functions. Constant term which arises from
linearization of a given nonlinear system is treated as a coefficient of
a stable zero dynamics. Parameters of the control are suboptimally
selected by maximizing the stable region in the sense of Lyapunov
with the aid of a genetic algorithm. This approach is applied to a
field excitation control problem of power system to demonstrate the
splendidness of the AACC. Simulation results show that the new
controller can improve performance remarkably well.

• Toshinori Nawata

• Augmented automatic choosing control
• nonlinear control
• genetic algorithm
• zero dynamics.

[1] Y. N. Yu, K. Vongsuriya and L. N. Wedman, "Application of an Optimal
Control Theory to a Power System”, IEEE Trans. Power Apparatus and
Systems, 89-1, 1970, pp.55–62.
[2] A. P. Sage and C. C. White III, "Optimum Systems Control (2nd edition)”,
Prentice-Hall, Inc., 1977.
[3] M. Vidyasagar, "Nonlinear Systems Analysis”, Prentice-Hall, Inc., 1978.
[4] K.Glover and J.C.Doyle, "State-Space Formula for All Stabilizing
Controllers that Satisfy and H∞-norm Bound and Relations to Risk
Sensitivity”, System & Letters, Vol.11-2, 1988, pp.167–172.
[5] A.Isidori, "Nonlinear Control Systems : An Introduction (2nd edition)”,
Springer-Verlag, 1989.
[6] H.Takata, "Automatic Choosing Control Design via GA for Nonlinear
Systems”, Proc.38th IEEE CDC, 1999, pp.5301–5306.
[7] T.Nawata and H.Takata, "An Augmented Automatic Choosing Control
Using Zero Dynamics for a class of Nonlinear Systems with Constrained
Input”, Proc. of 2002 International Symposium on Advanced Control of
Industrial Processes, 2002, pp.459–464.
[8] T.Nawata, "Design of an Augmented Automatic Choosing Control with
Constrained Input by Lyapunov Functions Using Gradient Optimization
Automatic Choosing Functions”, Proc. WASET, 2014 London (Accepted).
[9] R.Hanus,M.Kinnaert and J.-L.Henrotte, "Conditioning Technique, a
General Anti-windup and Bumpless Transfer Method”, Automatica,
Vol.23, No.6, 1987, pp.729–739.
[10] D. E. Goldberg, "Genetic Algorithms in Search, Optimization, and
Machine Learnings”, Addison-Wesley Pub. Co. Inc., 1989.