Title :
Nonlinear Quadratic Optimal Control for Cascaded Multilevel Static Compensators
Author :
Yucelen, Tansel ; Medagam, Peda V. ; Pourboghrat, Farzad
Author_Institution :
Southern Illinois Univ. Carbondale, Carbondale
fDate :
Sept. 30 2007-Oct. 2 2007
Abstract :
This paper presents a novel nonlinear quadratic optimal control technique for multiple-input, multiple-output (MIMO) cascaded multilevel static compensators (STATCOM), based on state-dependent Riccati equation (SDRE) technique. The proposed approach is applied online, using a gradient-type neural network algorithm for the computation of SDRE based nonlinear control. The algorithm is fast, computationally simple, and independent of initial conditions. This new control strategy is applied, in a detailed simulation, to the average d-q model of STATCOM to track a desired DC voltage and a reactive current, that demonstrates a relatively fast control ability and good dynamic performance.
Keywords :
Riccati equations; gradient methods; neurocontrollers; nonlinear control systems; optimal control; static VAr compensators; MIMO STATCOM; cascaded multilevel static compensators; d-q model; gradient-type neural network algorithm; nonlinear quadratic optimal control; reactive current; state-dependent Riccati equation; Automatic voltage control; Computational modeling; Computer networks; MIMO; Neural networks; Nonlinear equations; Optimal control; Riccati equations; STATCOM; Voltage control; Static compensator (STATCOM); nonlinear quadratic optimal control; online neural network computation; state-dependent Riccati equation (SDRE);
Conference_Titel :
Power Symposium, 2007. NAPS '07. 39th North American
Conference_Location :
Las Cruces, NM
Print_ISBN :
978-1-4244-1726-1
Electronic_ISBN :
978-1-4244-1726-1
DOI :
10.1109/NAPS.2007.4402360
