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Home / Journals / Automation, Control and Intelligent Systems / Predictive Control and Sliding Mode Control for Power Electronics and Motor Drives in Microgrids
Predictive Control and Sliding Mode Control for Power Electronics and Motor Drives in Microgrids

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Lead Guest Editor:
Siew-Chong Tan
University of Hong Kong, Hong Kong, China
Guest Editors
Yun Yang
University of Hong Kong
Hong Kong, China
Kai Yuen Cheong
Technological and Higher Education Institute of Hong Kong
Hong Kong, China
Wenxing Zhong
Zhejiang University
Hangzhou, Zhejiang, China
Cheng Zhang
University of Manchester
Manchester, UK
Sinan Li
University of Bath
Bath, UK
Shuangxia Niu
The Hong Kong Polytechnic University
Hong Kong, China
Introduction
Microgrids have emerged as a promising solution to accommodate the integration of renewable energy resources. However, the fluctuating outputs from renewable energy resources and variable power demand have posed many challenges such as voltage/frequency fluctuations. Meanwhile, with the increasing penetration of renewable energy resources and the associated electronic interfaces, the development of high-performance control strategies has attracted much attention in global academic and industry communities. So far, conventional control methods such as linear feedback control still lack sufficient control flexibility and intelligence to handle these fluctuations, resulting in stability problems and power quality issues. On the other hand, the advanced control strategies, i.e., predictive control and sliding mode control, have been very successful in power electronic converters and complex systems, such as electric machines. For predictive control, due to its fast-transient response and flexibility in considering different constraints, it shows huge potentials in microgrid applications. For sliding mode control, based on the mature theoretical framework, practical designs of sliding mode control are particularly suitable for the purpose of controlling power converters under various operating conditions of varied, nonlinear, and unpredictable renewable energy systems in microgrids.

Aims and Scope:

  1. Finite control set model predictive control (FCS-MPC) and/or continuous MPC for power converters
  2. Distributed predictive control of microgrids with renewable.
  3. Variable-frequency sliding mode control for grid-connected converters
  4. Constant-frequency pulse-width-modulation (PWM)-based sliding mode control for grid-connected converters
  5. Integrated predictive and sliding mode control for emerging technologies, e.g. wireless power transfer, in microgrids
  6. Distributed generations
  7. Power balance and management
  8. Power quality issue (harmonics, voltage/frequency deviations etc.)
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