Genetic Algorithm Based Improved Sub-Optimal Model Reduction in Nyquist Plane for Optimal Tuning Rule Extraction of PID and PI$^\lambda$D$^\mu$ Controllers via Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Das:2011:PACC,
  author =       "Saptarshi Das and Indranil Pan and Shantanu Das and 
                 Amitava Gupta",
  title =        "Genetic Algorithm Based Improved Sub-Optimal Model
                 Reduction in Nyquist Plane for Optimal Tuning Rule
                 Extraction of PID and {PI{$^\lambda$}D{$^\mu$}}
                 Controllers via Genetic Programming",
  booktitle =    "International Conference on Process Automation,
                 Control and Computing (PACC 2011)",
  year =         "2011",
  month =        "20-22 " # jul,
  address =      "Coimbatore",
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, GA, GP,
                 H2-norm based reduced order modelling techniques,
                 Nyquist based sub-optimal model reduction, Nyquist
                 plane, PID controllers, Pareto optimal front, control
                 signal, fractional order PI D, controllers, optimal
                 tuning rule extraction, weighted integral error index,
                 control system synthesis, optimal control, reduced
                 order systems, signal processing, three-term control",
  isbn13 =       "978-1-61284-765-8",
  DOI =          "doi:10.1109/PACC.2011.5978962",
  URL =          "http://arxiv.org/abs/1202.5686",
  URL =          "http://arxiv.org/pdf/1202.5686v1",
  size =         "6 pages",
  abstract =     "Genetic Algorithm (GA) has been used in this paper for
                 a new Nyquist based sub-optimal model reduction and
                 optimal time domain tuning of PID and fractional order
                 (FO) PI lambda D mu controllers. Comparative studies
                 show that the new model reduction technique outperforms
                 the conventional H2-norm based reduced order modelling
                 techniques. Optimum tuning rule has been developed next
                 with a test-bench of higher order processes via Genetic
                 Programming (GP) with minimum value of weighted
                 integral error index and control signal. From the
                 Pareto optimal front which is a trade-off between the
                 complexity of the formulae and control performance, an
                 efficient set of tuning rules has been generated for
                 time domain optimal PID and PID controllers.",
  notes =        "Also known as \cite{5978962}",
  oai =          "oai:arXiv.org:1202.5686",
}

Genetic Programming entries for Saptarshi Das Indranil Pan Shantanu Das Amitava Gupta

Citations