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Online ISSN 1751-8652 Print ISSN 1751-8644

IET Control Theory & Applications

Volume 10, Issue 12, 08 August 2016


Volume 10, Issue 12

08 August 2016

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    • Guest Editorial
      Convergence performance oriented data-driven tuning method for parameterised controller design with cases investigation
      Online reinforcement learning control by Bayesian inference
      Using reinforcement learning techniques to solve continuous-time non-linear optimal tracking problem without system dynamics
      Data-driven optimal control of operational indices for a class of industrial processes
      Data-driven optimal terminal iterative learning control with initial value dynamic compensation
      Model-independent approach for short-term electric load forecasting with guaranteed error convergence
      Application of fractional order iterative learning controller for a type of batch bioreactor
      Local learning-based model-free adaptive predictive control for adjustment of oxygen concentration in syngas manufacturing industry
      Multi-input–multi-output system experimental validation of model-free control and virtual reference feedback tuning techniques
      Reagent dosages control based on bubble size characteristics for flotation process
      Improved data driven model free adaptive constrained control for a solid oxide fuel cell
      Hybrid intelligent modelling and simulation for cold tandem rolling process
      Data-driven policy iteration algorithm for optimal control of continuous-time Itô stochastic systems with Markovian jumps
      Sampled-data-based adaptive optimal output-feedback control of a 2-degree-of-freedom helicopter
      Distributed adaptive optimal regulation of uncertain large-scale interconnected systems using hybrid Q-learning approach
      Adaptive cyber-physical system attack detection and reconstruction with application to power systems
      Iterative tuning strategy for setting phase splits with anticipation of traffic demand in urban traffic network
      Controller synthesis for negative imaginary systems: a data driven approach

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