Emad Ali

On-line tuning strategy for model predictive controllers

This paper presents an intuitive on-line tuning strategy for linear Model Predictive Control (MPC) algorithms. The tuning strategy is based on the linear approximation between the closed-loop predicted output and the MPC tuning parameters. By direct utilization of the sensitivity expressions for the closed-loop response with respect to the MPC tuning parameters, new values of the tuning parameters can be found to steer the MPC feedback response inside predefined time-domain performance specifications. Hence, the algorithm is cast as a simple constrained least squares optimization problem which has a straightforward solution. The simplicity of this strategy makes it more practical for on-line implementation. Effectiveness of the proposed strategy is tested on two simulated examples. One is a linear model for a three-product distillation column and the second is a non-linear model for a CSTR. The effectiveness of the proposed tuning method is compared to an exiting offline tuning method and showed superior performance.

Heuristic On-Line Tuning for Nonlinear Model Predictive Controllers Using Fuzzy Logic

Abstract In this paper a systematic mechanism for on-line tuning of the non-linear model predictive controllers is presented. The proposed method automatically adjusts the prediction horizon P , the diagonal elements of the input weight matrix Λ, and the diagonal elements of the output weight matrix Γ for the sake of good performance. The desired good performance is cast as a time-domain specification. The control horizon ( M ) is left constant because of the importance of its relative value with respect to P . The concepts from fuzzy logic are used in designing the tuning algorithm. In the mechanism considered here, predefined fuzzy rules represent available tuning guidelines and the performance violation measure in the form of fuzzy sets determine the new tuning parameter values Therefore, the tuning algorithm is formulated as a simple and straightforward mechanism, which makes it more appealing for on-line implementation. The effectiveness of the proposed tuning method is tested through simulated implementation on three non-linear process examples. Two of these examples possess open-loop unstable dynamics. The result of the simulations shows that this method is successful and promising.

Model reduction and robust control of multi-stage flash (MSF) desalination plants

An orthogonal collocation method is used for the reduction of a large nonlinear model of a multi-stage flash (MSF) desalination plant. The real plant located in Saudi Arabia consists of 19 stages in the heat recovery section and three in the heat rejection section. It is shown that three collocation points, i.e., two for the heat recovery section and one for the heat rejection section, are sufficient for a good representation of the full-order model for both steady-state and dynamic behavior. The reduced model is then used for a robust controller design of the plant using a constrained nonlinear model predictive control (NLMPC) strategy. Numerical simulations show that the controlled system obtained when the reduced model is used for output prediction yields the same performances as with the full-order model but with a considerable reduction in the computational time and a much easier tuning of the controller.

pH Control Using PI Control Algorithms With Automatic Tuning Method

pH control is quite difficult due to the non-linearity of the neutralization process. In this case, tuning the standard PI controller is a must to achieve a stable feedback A response. This paper, thus, addresses the application of an automatically tuned PI algorithm to stabilize the pH-value of a pH neutralization process. The proposed adapted PI algorithm uses a simple model for the process to predict the pH closed-loop response and its sensitivity to the PI settings. The information obtained is directly used to adjust the PI tuning parameters online in order to produce a pH response that satisfies a pre-defined time-domain specification. The simulation results of the proposed method are compared with those obtained by the standard PI, gain scheduling (GS) and globally linearizing (GLC) algorithms. The comparison showed a successful and promising implementation of the proposed strategy.

Determination of cost-effective operating condition for CO2 capturing using 1-butyl-3-methylimidazolium tetrafluoroborate ionic liquid

Abstract1-Butyl-3-methylimidazolium tetrafluoroborate ([BMIM][BF4]) ionic liquid (IL) is considered for CO2 capturing in a typical absorption/stripper process. The use of ionic liquids is considered to be cost-effective because it requires less energy for solvent recovery compared to other conventional processes. A mathematical model was developed for the process based on Peng-Robinson (PR) equation of state (EoS). The model was validated with experimental data for CO2 solubility in [BMIM][BF4]. The model is utilized to study the sorbent effect and energy demand for selected operating pressure at specific CO2 capturing rates. The energy demand is expressed by the vapor-liquid equilibrium temperature necessary to remove the captured CO2 from the spent solvent in the regeneration step. It is found that low recovery temperature can be achieved at specific pressure combination for the absorber/stripper units. In fact, the temperature requirement is less than that required by the typical monoethanolamine (MEA) solvent. The effect of the CO2 loading in the sorbent stream on the process performance is also examined.

Understanding the operation of industrial MSF plants Part I: Stability and steady-state analysis

This paper deals with expanding the knowledge about the operation of multi-stage flash (MSF) desalination processes. This was achieved through stability and steady-state analysis conducted on a simulated model for the MSF plant. The model was developed and validated using steady-state plant data. The stability analysis was based on the eigenvalues of the linearized version of the model, which revealed that the MSF plant is normally internally stable. The steady-state analysis investigated the effect of each process input on the process key variables. The combined effect of two inputs at a time was also examined. The steady-state analysis was found useful to locate economically favorable operating conditions and to locate conditions at which undesirable brine level may occur. The steady-state analysis is also useful to study the controllability of the MSF plant, which helps in enhanced control design.

Optimization-based periodic forcing of RO desalination process for improved performance

AbstractThe performance of a tubular reverse osmosis (RO) process for water desalination is investigated using periodically forced feed parameters. The study was performed using a dynamic model that was developed and validated in a previous work. Simultaneous forcing of feed pressure and flow rate were studied. Fully symmetric rectangular pulses were used for input forcing because of their applicability for digital control implementation. It was found that the simultaneous periodic operation of the RO inputs improves its performance in the sense of higher permeate flow rate and reduced salt concentration. Increasing the pressure forcing amplitude will further enhance the performance; however, the attainable performance is limited by the constraints on the operating pressure. Depending on the RO unit constraints and characteristics, a maximum increase in permeate flow rate up to 42% and reduction in salt concentration of about 20% could be obtained.

A long-term forecast of water demand for a desalinated dependent city: case of Riyadh City in Saudi Arabia

Abstract The forecast of long-term water demand is important for the planning of future requirements for water supply, distribution, and wastewater systems. The forecast is particularly important for arid countries such as Saudi Arabia which rely on costly desalination plants to satisfy the growing water demand. This study develops a model for forecasting water demand for Riyadh city, the capital of the country. The development of a sound forecast model is complicated by the uncertainties associated with key factors, such as the population growth and the economic activity, which is largely dependent on fluctuating oil prices. The forecast is also made difficult by the inefficient management of unaccounted-for-water (UFW). All these factors limit the usefulness of any deterministic forecast model. This paper develops a probabilistic forecast model that incorporates explicitly the uncertainties associated with population growth, household size, household income as well as conservation measures, and UFW mana...

Understanding the operation of industrial MSF plants Part II: Optimization and dynamic analysis

This paper is a continuation of Part I, which aims at widening the knowledge about MSF operation. The investigation includes studying the set-point optimization of an MSF plant. This is achieved by optimizing the steady-state model of the plant to determine the optimal operating conditions. The objective function is designed such that it determines the feasible values for the plant operational parameters that maximize the performance ratio. The investigation also includes studying the dynamic behavior of the process during open-loop and closed-loop operations. The dynamic analysis in both cases focuses on investigating the source and existence of operation stability due to blow-through or liquid pile-up. The entire analysis is based on simulation of a previously validated model for an MSF plant.

Modeling of CO2 Solubility in Selected Imidazolium-Based Ionic Liquids

This study explores the use of COSMO-RS model and Peng-Robinson (PR) equation of state (EoS) to predict the solubility of carbon dioxide (CO2) in specific ionic liquids (ILs). COSMO-RS was employed to estimate of CO2 solubility at atmospheric pressure in eight imidazolium-based ILs resulting from the combination of ethyl, butyl, hexyl, and octyl-imidazolium cations with two anions: bis(trifluoromethylsulfonyl)imide ([Tf2N]) and Trifluoromethanesulfonate ([TFO]). The results indicated relatively acceptable qualitative consistency between the experimental and predicted values. The PR EoS was employed at high pressure by tuning the interaction parameters to fit the experimental data reported in the literature. The model demonstrated excellent accuracy in predicting the solubility of CO2 at pressure values less than the critical pressure of CO2; however, at higher pressures, the calculated solubility diverged from the experimental values. Furthermore, the type of anion and cation used in the IL affected the performance of the PR EoS.