An adaptive neuro-control approach for multi-machine power systems

摘要: Abstract We investigate an adaptive neuro-control approach, namely goal representation heuristic dynamic programming (GrHDP), and study the nonlinear optimal control on multi-machine power system. Compared with conventional approaches, proposed controller conducts learning assumes unknown of system mathematic model. Besides, design can provide reward signal that guides performance over time. In this paper, we integrate novel neuro-controller into supplementary signals. For fair comparative studies, include (HDP) approach under same conditions. The damping performances without stabilizer (PSS) are also presented for comparison. Simulation results verify investigated achieve improved in terms transient stability robustness different fault