... completely by using the DSMC with a small switching gain. Consider the following assumptions, which are widely used [( 24 25 26 )]: 09 12 2009 13 03 2011 11 11 2011 11 11 2011 adaptive control learning (artificial intelligence) machine control neurocontrollers nonlinear...

... developed based on proposed schemes sustains the performance under parametric uncertainties and disturbances. 04 06 2009 10 10 2010 06 04 2011 06 04 2011 evolutionary computation fuzzy reasoning learning (artificial intelligence) statistical analysis learning fuzzy rule...

... direction needs to be maintained in high-speed AFM-imaging. atomic force microscopy electric current control feedforward learning (artificial intelligence) neurocontrollers position control 18 06 2008 27 04 2009 06 11 2009 06 11 2009 2009 American Society...

... result of operation planning using the GA. 13 09 2007 28 10 2008 19 03 2009 biofuel genetic algorithms hydrogen production learning (artificial intelligence) proton exchange membrane fuel cells solar absorber-convertors solar radiation steam bioethanol solar reforming...

... nonlinear hydraulic manipulators performing a common task. 23 06 2006 25 01 2007 control engineering computing decentralised control hydraulic actuators learning (artificial intelligence) manipulators motion control neural nets One aspect of robotics research that continues...

... relationships between process input–output variables is steadily increasing. A good model of the process is indispensable for the successful optimization and model-based control 1 2 3 . grinding fuzzy neural nets learning (artificial intelligence) radial basis function networks least squares...

... 2004 learning systems uncertain systems iterative methods learning (artificial intelligence) linear systems adaptive control stability inverse problems Iterative learning control (ILC) refers to a class of self-tuning controllers where the system performance of a specified task...

... , McGraw-Hill , New York. Hecht-Nielsen , R. , 1989 , Neuralcomputing , Addison-Wesley , New York. 26 03 2003 02 05 2004 mechanical engineering computing learning (artificial intelligence) helicopters blades vibrations Helicopter track and balance...

... constraints, is recently applied to chemical process monitoring 4 . internal combustion engines intelligent sensors fault diagnosis feedforward neural nets learning (artificial intelligence) real-time systems 31 June 1999 Contributed by the Dynamic Systems and Control Division...

.... Voulgaris. 10 February 1999 flexible manipulators multivariable control systems learning (artificial intelligence) feedforward control nonlinearities optimal control filtering theory delay filters Having flexibility in a mechanical manipulator will degrade trajectory tracking...