Digital Control Algorithms

  • Spyros G. Tzafestas
  • J. K. Pal
Part of the Microprocessor-Based Systems Engineering book series (ISCA, volume 5)


The last three decades have seen rapid development in modern control theory and microprocessors. Application of newly developed control algorithms in Industrial process control has gained popularity due to microprocessor based control systems. In this chapter all categories of control algorithms which have gained popularity amongst industrial users or which are industrially implementable are covered. We have first covered control algorithms for single-input single-output (SISO) systems and then multi-input multi-output (MIMO) systems. Three term controllers, time delay compensation techniques and fuzzy logic controllers, etc., have been discussed for SISO plants. Predictive, adaptive, optimal and state feedback controllers have been covered for both SISO and MIMO plants. We have discussed auto tuning techniques for SISO PID controllers and also briefly expert control systems. Algorithms have been described in their digital implementation form. Implementation of control algorithms in industrially available distributed digital control system has been discussed. A brief report has been given for actual implementation of some algorithms in industrial plants and benefits due to this implementation have been highlighted. In particular applications of optimal control and optimal filtering in power industry in UK and power, cement and steel industry in Japan and predictive control techniques in petroleum industries in North America have been mentioned while describing the particular algorithm. Recent research results to pool resources of linear quadratic gaussian design popular in power, cement and steel industry and predictive control (model algorithmic control and internal model control) popular in petroleum industries to evolve a better approach to controller design have been highlighted.


Thermal Power Plant Fuzzy Logic Controller Optimal Controller State Feedback Controller Prediction Horizon 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Kluwer Academic Publishers 1990

Authors and Affiliations

  • Spyros G. Tzafestas
    • 1
  • J. K. Pal
    • 2
  1. 1.Control and Robotics Group Computer Engineering DivisionNational Technical University of AthensAthensGreece
  2. 2.Engineering Technology and Development DivisionEngineers India LimitedNew DelhiIndia

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