Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multiple generators on the electric power grid are presented. The feedback variables are completely based on local measurements. Simulations on a three-machine power system demonstrate that the neurocontrollers are much more effective than conventional PID controllers, the automatic voltage regulators and the governors, for improving the dynamic performance and stability under small and large disturbance
Turbogenerators are nonlinear time varying systems. This paper presents the design of a neurocontrol...
This paper reports on the simulation and practical studies carried out on a single turbogenerator co...
A novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system,...
The design and real-time implementation of derivatives adaptive critic based neurocontrollers that r...
The design of optimal neurocontrollers that replace the conventional automatic voltage regulators fo...
The increasing complexity of the modern power grid highlights the need for advanced modeling and con...
This paper presents the design of two separate continually online trained (GOT) artificial neural ne...
Based on derivative adaptive critics, a novel nonlinear optimal voltage/excitation control for a mul...
This paper presents the design of two separate continually online trained (COT) neurocontrollers for...
Based on Dual Heuristic Programming (DHP), a real-time implementation of a neurocontroller for excit...
This paper presents the design and practical hardware implementation of optimal neurocontrollers tha...
The increasing complexity of the modern power grid highlights the need for advanced modeling and con...
The increasing complexity of a modern power grid highlights the need for advanced system identificat...
This paper presents the design of an optimal neurocontroller that replaces the conventional automati...
A review of the applications of intelligent control to replace/augment the conventional excitation a...
Turbogenerators are nonlinear time varying systems. This paper presents the design of a neurocontrol...
This paper reports on the simulation and practical studies carried out on a single turbogenerator co...
A novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system,...
The design and real-time implementation of derivatives adaptive critic based neurocontrollers that r...
The design of optimal neurocontrollers that replace the conventional automatic voltage regulators fo...
The increasing complexity of the modern power grid highlights the need for advanced modeling and con...
This paper presents the design of two separate continually online trained (GOT) artificial neural ne...
Based on derivative adaptive critics, a novel nonlinear optimal voltage/excitation control for a mul...
This paper presents the design of two separate continually online trained (COT) neurocontrollers for...
Based on Dual Heuristic Programming (DHP), a real-time implementation of a neurocontroller for excit...
This paper presents the design and practical hardware implementation of optimal neurocontrollers tha...
The increasing complexity of the modern power grid highlights the need for advanced modeling and con...
The increasing complexity of a modern power grid highlights the need for advanced system identificat...
This paper presents the design of an optimal neurocontroller that replaces the conventional automati...
A review of the applications of intelligent control to replace/augment the conventional excitation a...
Turbogenerators are nonlinear time varying systems. This paper presents the design of a neurocontrol...
This paper reports on the simulation and practical studies carried out on a single turbogenerator co...
A novel nonlinear optimal controller for a static compensator (STATCOM) connected to a power system,...