Abstract:The design of the proposed algorithm relies on three basic ideas: (1) finding a model-based controller so that for any stable process of proportional type, the closed-loop controller output to a step reference has a step shape (or close to this form) and removes the steady-state error; (2) refining the controller structure so that the initial value of the controller output to a step reference is K times its final value, where K is a tuning parameter with standard value 1; (3) extending the controller structure to address integral processes and some unstable processes by turning them into stable compensated processes of proportional type. The overall controller is a series connection P-IMC of two systems: one of pure proportional type and another one of IMC type. There is a simple procedure to verify online if the model parameters (steady-state gain, time delay and transient time) have suitable values and to adjust them to improve the model. As the PID control algorithm, the proposed method is quasi-universal and practical, but it is superior by its control performance and the simplicity of the tuning procedure (which enables poorly trained workers to easily operate the control system). Also, it is more practical than the classical IMC algorithm because its equations have a unique form for all process types (as the PID algorithm), and has a control gain as tuning parameter instead of a filter time constant. Several applications are given to show the effectiveness of the algorithm for different types of process.

Gas sweetening unit, also known as acid gas removal unit, is a wide used unit in refineries and petrochemical plants and refers to a group of processes that use different amines such DiEthanolAmine (DEA) to remove the hydrogen sulfide (H 2 S) from gases, in order to use them as fuel to different furnaces from other processing units. If the hydrogen sulfide is not well removed, will lead to furnaces tubular corrosion and therefore will generate loss in refractory properties. Also, the emission values of the exhaust gases will not be in accordance with the environmental regulations. The paper outlines the main results obtained by authors concerning the advanced control solution for a refinery gas sweetening unit and contains three parts. The first part outlines the results of the dynamic gas sweetening process investigation using HYSYS ® simulation software. The second part presents the proposed structure of the advanced control system and the third part outlines the results obtained using the control structure in order to remove as good as possible the H 2 S content from residual gases.

This paper presents the extension of the hardware-software experimental system SENFpHCTRL initially developed for wastewater pH control, for monitoring other parameters (total suspended solids, extractable, biochemical and chemical oxygen demand, phenols and chlorides) from other chemical processes of a treatment plant, such as: precipitation, coagulation and flocculation, oxidation and reduction (processes briefly presented at the begining of the paper). The process of expanding the SENFpHCTRL system involved the adding to the initial expert system of a set of heuristic knowledge for other parameters and the development of the system graphical interface. It is also presented the adapted form of the system hardware component at PC and microcontroller level and the results of the simulations made with the extended system.

We extend the right and left convex function theorems to weighted Jensen's type inequalities, and then combine the new theorems in a single one applicable to a half convex function f(u), defined on a real interval Á and convex for u ≤ s or u ≥ s, where s ∈ Á . The obtained results are applied for proving some open relevant inequalities.

The opportunity analysis of using two Proportional-Integral (PI) controllers, tuned with Skogestad�s variant of Simple Internal Model Control based (SIMC) method, for controlling the top and bottom compositions of a propylene/propane distillation column represents the paper aim. The SIMC method for PID controllers is the simplest and extremely good model in tuning procedures. Because the distillation process is nonlinear, the process model is described by a reunion of different linear models, for the different process operating ranges and, for each operating range, different sets of controllers� tuning parameters are computed using SIMC tuning method. In order to validate the experimental results a comparison is made with the case when the PI controllers are tuned using Ziegler-Nichols (ZN) method that uses the step response and process approximation exactly as Skogestad�s variant of SIMC.