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ABSTRACT: This paper presents the new development of the boiler-turbine coordinated control strategy using fuzzy reasoning and autotuning techniques. The boiler-turbine system is a very complex process that is a multivariable, nonlinear, slowly time-varying plant with large settling time and a lot of uncertainties. As there exist strong couplings between the main steam pressure control loop and the power output control loop in the boiler-turbine unit with large time-delay and uncertainties, automatic coordinated control of the two loops is a very challenging problem. This paper presents a new coordinated control strategy (CCS) which is organized into two levels: a basic control level and a high supervision level. Proportional-integral derivative (PID) type controllers are used in the basic level to perform basic control functions while the decoupling between two control loops can be realized in the high level. A special subclass of fuzzy inference systems, called the Gaussian partition with evenly (GPE) spaced midpoints systems, is used to self-tune the main steam pressure PID controller's parameters online based on the error signal and its first difference, aimed at overcoming the uncertainties due to changing fuel calorific value, machine wear, contamination of the boiler heating surfaces and plant modeling errors. For the large variation of operating condition, a supervisory control level has been developed by autotuning technique. The developed CCS has been implemented in a power plant in China, and satisfactory industrial operation results demonstrate that the proposed control strategy has enhanced the adaptability and robustness of the process. Indeed, better control performance and economic benefit have been achieved.
IEEE Transactions on Control Systems Technology 12/2005; · 1.77 Impact Factor
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Control and Automation, 2002. ICCA. Final Program and Book of Abstracts. The 2002 International Conference on; 02/2002
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ABSTRACT: For original paper see ibid., vol. 47, no. 10, p. 1227-1237 (2000 ). In Theorem 1 of the aforementioned paper, it is claimed that the correlation matrix of the lattice backward predictor error vector is always better conditioned than that of the wide sense stationary input signal. The proof of the result, unfortunately, is based on an incorrect reasoning. In this comment, we shall give a rigorous proof of the result for the optimal lattice filters.
IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing 11/2001;
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ABSTRACT: This paper presents a new control-loop configuration criterion for multivariable processes. Both the steady-state and transient information of the process transfer function are investigated. A new interaction measurement, relative normalized gain array, is proposed for evaluating control-loop interactions. Consequently, a new loop pairing criterion based on the relative normalized gain array is proposed for control structure configuration. The main contribution of this work is that it systematically analyzed the process transferring characteristics from both steady-state and transient perspectives and derived a feasible solution for the problem. Several examples, for which the conventional relative gain array based loop pairing criterion gives an inaccurate interaction assessment, are employed to demonstrate the effectiveness of the proposed interaction measure and loop pairing criterion.
Journal of Process Control.
