19 March 2016

Call for papers: "Observer-based Fuzzy, Neural and Adaptive Control: Advances and Applications"

For a special issue of the International Journal of Automation and Control.

In practice, the implementation of control input is usually faced with the problem of nonlinearity in control input due to non-ideal characteristics of actuators used in physical implementations. Adaptive control theory for nonlinear systems has attracted much attention during the past two decades. Recently, adaptive control based on universal approximations such as fuzzy logic systems, RBF neural networks or fuzzy-neural networks have been considered extensively in the control problems of complex and ill-defined nonlinear systems in the presence of incomplete knowledge of the plant. Observer-based robust adaptive universal approximation control schemes are very useful for tackling the problem of robust stability and the tracking control for a class of uncertain nonlinear SISO systems and MIMO systems with or without time delays. Also, adaptive universal approximation control schemes have impact for a class of nonlinear systems with dead-zone and multiple time-delays based on dynamic surface control technique.

The overall aim of this special issue is to compile the latest research and developments and up-to-date issues and challenges in the field of observer-based universal approximation adaptive control schemes. Proposed submissions should be original and should present novel in-depth fundamental research contributions either from a methodological perspective or from an application point of view.

The issue will carry revised and substantially extended versions of selected papers presented at the 3rd International Conference on Automation, Control Engineering and Computer Science (ACECS-2016), but we are also inviting other experts to submit articles for this call.

Suitable topics include but are not limited to:
  • Adaptive control
  • Robust control
  • Output-feedback control
  • Fuzzy control
  • Fuzzy observer
  • Neural-fuzzy control
  • Fuzzy-neural control
  • Hybrid control systems
  • Chaos control and synchronisation
  • System identification
  • Nonlinear control systems
  • Iterative learning control
  • Time delayed uncertainty

Important Dates
Submission deadline: 31 July, 2016

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