Programmed trajectory motion control for synchronous generators

Yu V. Khrushchev, I. Yu Khrushchev*, A. V. Prokhorov, N. A. Belyaev, A. S. Vasiliev

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The paper presents the concept of adaptive control in electrical power systems, based on programmed trajectory motion of synchronous generators. The feasibility of the method is tested in a range of simulation experiments. The key feature of the technique is the use of a simple reference model which defines the dynamics of the controlled parameters. As a result, the voltage vector angle, velocity and acceleration are delivered to the exact, rather than approximate, target values in a predictable, coordinated, robust and efficient manner. Compared to other adaptive methods, such as model predictive control, the technique makes a more efficient use of computational resources, which makes it particularly beneficial if implemented at lower levels of control system hierarchy. It also shows a promising level of robustness against disturbances during the control process. We envisage that the most relevant practical applications are the stabilization and synchronization of small to medium size synchronous machines connected to distribution grid, and management (corrective control and resynchronization) of islanded sub-systems, such as microgrids. Simulations also indicate relatively short control time and improved stability against perturbations. With a proper choice of reference model, the need for bi-polar control action does not arise and the target values are achieved by uni-polar action only. Both the stabilization and the synchronization tasks are accomplished by means of one control algorithm, which improves the quality of control, especially in post-emergency operating conditions. The time-domain modeling results reported in the paper were obtained from software-based simulators.

Original languageEnglish
Article number105884
JournalInternational Journal of Electrical Power and Energy Systems
Early online date20 Feb 2020
Publication statusPublished - Jul 2020


  • Adaptive control
  • Distributed generation
  • Power system control
  • Programmed trajectory
  • Synchronization
  • Synchronous generators


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