Based on Dual Heuristic Programming (DHP), a real-time implementation of a neurocontroller for excitation and turbine control of a turbogenerator in a multimachine power system is presented. The feedback variables are completely based on local measurements. Simulation and real-time hardware implementation on a three-machine system demonstrate that the DHP neurocontroller is much more effective than conventional PID controllers, the automatic voltage regulator, power system stabilizer and the governor, for improving dynamic performance and stability under small and large disturbances
The design and real-time implementation of derivatives adaptive critic based neurocontrollers that r...
The increasing complexity of the modern power grid highlights the need for advanced modeling and con...
In this paper, the dual heuristic programming (DHP) optimization algorithm is applied for the design...
The design of nonlinear optimal neurocontrollers that replace the conventional automatic voltage reg...
The design of nonlinear optimal neurocontrollers that replace the conventional automatic voltage reg...
The design of optimal neurocontrollers that replace the conventional automatic voltage regulators fo...
The design of nonlinear optimal neurocontrollers that replace the conventional automatic voltage reg...
This paper presents the design and practical hardware implementation of optimal neurocontrollers tha...
This paper presents the design of a neurocontroller for a turbogenerator that augments/replaces the ...
This paper presents the design of an optimal neurocontroller that replaces the conventional automati...
This paper presents the design of an optimal neurocontroller that replaces the conventional automati...
Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multipl...
Turbogenerators are nonlinear time varying systems. This paper presents the design of a neurocontrol...
This paper presents the design of two separate continually online trained (GOT) artificial neural ne...
This paper presents the design of two separate continually online trained (COT) neurocontrollers for...
The design and real-time implementation of derivatives adaptive critic based neurocontrollers that r...
The increasing complexity of the modern power grid highlights the need for advanced modeling and con...
In this paper, the dual heuristic programming (DHP) optimization algorithm is applied for the design...
The design of nonlinear optimal neurocontrollers that replace the conventional automatic voltage reg...
The design of nonlinear optimal neurocontrollers that replace the conventional automatic voltage reg...
The design of optimal neurocontrollers that replace the conventional automatic voltage regulators fo...
The design of nonlinear optimal neurocontrollers that replace the conventional automatic voltage reg...
This paper presents the design and practical hardware implementation of optimal neurocontrollers tha...
This paper presents the design of a neurocontroller for a turbogenerator that augments/replaces the ...
This paper presents the design of an optimal neurocontroller that replaces the conventional automati...
This paper presents the design of an optimal neurocontroller that replaces the conventional automati...
Based on derivative adaptive critics, neurocontrollers for excitation and turbine control of multipl...
Turbogenerators are nonlinear time varying systems. This paper presents the design of a neurocontrol...
This paper presents the design of two separate continually online trained (GOT) artificial neural ne...
This paper presents the design of two separate continually online trained (COT) neurocontrollers for...
The design and real-time implementation of derivatives adaptive critic based neurocontrollers that r...
The increasing complexity of the modern power grid highlights the need for advanced modeling and con...
In this paper, the dual heuristic programming (DHP) optimization algorithm is applied for the design...