Optimal Operator Training Reference Models for Human-in-the-loop Systems
- Wan-Lin Hu, SLAC National Accelerator Laboratory, Stanford University, Stanford, California, United States
- Claudio Rivetta, Energy Sciences Directorate, SLAC National Accelerator Laboratory, Menlo Park, California, United States
- Erin MacDonald, Department of Mechanical Engineering, Stanford University, Stanford, California, United States
- David P. Chassin, Energy Sciences Directorate, SLAC National Accelerator Laboratory, Menlo Park, California, United States
AbstractThe human operator is an integral part of a stable and safe power system. While there is increasing attention paid to automation improvements, the importance of understanding and training human operators may be understated. This paper discusses a project to enhance operator training programs by evaluating human performance relative to a reference operator model identified using optimal control theory. Along with establishing a simple computer-based operator workstation for future training purpose, this paper describes the optimal control response design methodology for a human-in-the-loop power system experiment. The overall system model is presented. An optimal controller synthesis methodology is applied to the model system and the optimal controller is designed. The performance of the optimal controller is then compared to human subject performance.
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