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This work extends the concept of relative normalized gain array (RNGA) and proposes a systematic approach to designing decentralized proportional−integral−derivative (PID) control for multi-input−multi-output (MIMO) processes containing integrators and/or differentiators. By determining the input−output-pairing using the relative gain array (RGA)−Nederlinski index (NI)−RNGA criterion, equivalent transfer functions (ETFs) for the selected input−output pairs are derived by utilizing the RGA and RNGA information, which has incorporated the information on loop interactions. Based on the ETFs, decentralized PID controllers are tuned to stabilize the MIMO system independently. The proposed approach is simple, easy to understand, and easy to implement by field engineers. Three industrial MIMO processes with different dimensions and interaction modes are employed to demonstrate the efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Based on the theory of equivalent transfer functions (ETFs), this work proposes a novel partial decoupling control technique for multivariable processes. By measuring the effect of each ETF element in decoupling control, a partial decoupling control structure selection criterion is proposed with the aims that the decoupler has the least complexity and that overall system performance is satisfied. The ETF parameters are then obtained under certain constraints. Consequently, a systematic design procedure is proposed in order to obtain a stable, proper, and causal partial decoupler matrix. Simulation results of several multivariable processes with different interaction characteristics are provided to demonstrate the simplicity and effectiveness of the design method. [ABSTRACT FROM AUTHOR]