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This work reveals the applicability of a relatively new optimization technique, Leapfrogging, for both nonlinear regression modeling and a methodology for nonlinear model-predictive control. Both are relatively simple, yet effective. The application on a nonlinear, pilot-scale, shell-and-tube heat exchanger reveals practicability of the techniques. [ABSTRACT FROM AUTHOR]

Abstract: Nonlinear, adaptive, process-model based control is demonstrated in a cascaded single-input–single-output mode for pressure drop control in a pilot-scale packed absorption column. The process is shown to be nonlinear. Control is demonstrated in both servo and regulatory modes, for no wind-up in a constrained situation, and for bumpless transfer. Model adaptation is demonstrated and shown to provide process insight. The application procedure is revealed as a design guide to aid others in implementing process-model based control. [Copyright &y& Elsevier]

Abstract: This pilot-scale heat exchanger demonstration compares two relatively simple nonlinear model-based control strategies to conventional proportional-integral (PI) control. The two nonlinear controllers, generic model control (GMC) and process-model based control (PMBC), use a first-principles model thereby providing characterization of the nonlinear process throughout the operating range. There are two approaches to GMC, one uses a dynamic model, the other a steady-state model. This work uses the steady-state model; accordingly, will use the term GMC-SS, which can be classified as output characterization for a PI controller, making it relatively simple to implement. PMBC uses a dynamic model and adapts to represent the process. These two nonlinear controllers were selected for this application evaluation because of their simplicity (they can be implemented in-house within many commercial control systems), diversity (steady-state and dynamic models), and demonstrated utility for control of nonlinear single-input–single-output processes. The application and results are presented and discussed. Summarizing the results: Within a small temperature operating range PI provides good control, but over the full operating range, the nonlinear and variable delay of the process lead to poor control with PI. GMC can handle the nonlinear issues, but using the convenient steady-state model; it also, provides poor control because of the variable delay associated with flow rate. PMBC was able to provide good control throughout the entire operating range. PMBC has a further advantage of only having one tuning coefficient, while PI and GMC-SS have two. [Copyright &y& Elsevier]

Abstract: Although standards for orifice flow meter design, installation, and calibration are supported herein, noncompliant devices exist in many pilot-, lab-scale, and on-board applications. For these, a common calibration practice is to preserve the ideal square root relation and determine a device specific discharge coefficient value. This work provides theoretical and empirical analyses to support relaxing the square root relation between orifice pressure drop and flow rate for noncompliant devices. The resulting power law relation is shown to improve accuracy, precision, and rangeability. Whether a device specific square root or power law model is used, it requires off-line or in-line calibration data. As such, a power law calibration model may only be useful for on-board and small-scale applications. [Copyright &y& Elsevier]

Abstract: This work investigates the use of a statistically based override on an automatic controller. The objective is to temper controller action, and to obtain a better balance of variance reduction in both controlled and manipulated variables than is currently obtained with conventional filtering. Experimental results on a pilot-scale flow loop demonstrate the benefit. Results are supported by both simulation and theoretical analysis. [Copyright &y& Elsevier]

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