-
[show abstract]
[hide abstract]
ABSTRACT: Identification of stable parametric models from input-output data of a process (stable) is an essential task in system identification. For a stable process, the identified parametric model may be unstable due to one or more of the following reasons: 1) presence of noise in the measurements, 2) plant disturbances, 3) finite sample effects 4) over/under modeling of the process and 5) nonlinear distortions. Therefore, it is essential to impose stability conditions on the parameters during model estimation. In this technical note, we develop a computationally efficient approach for the identification of global ARX parameters with guaranteed stability. The computational advantage of the proposed approach is derived from the fact that a series of computationally tractable quadratic programming (QP) problems are solved to identify the globally optimal parameters. The importance of identifying globally optimal stable model parameters is high lighted through illustrative examples; this does not seem to have been discussed much in the literature.
IEEE Transactions on Automatic Control 07/2011; · 2.11 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: A common practice in a system identification exercise is to perturb the system of interest and use the resulting data to build a model. The problem of interest in this contribution is to synthesize an input signal that is maximally informative for generating good quality models while being “plant friendly,” i.e., least hostile to plant operation. In this contribution, limits on input move sizes are the plant friendly specifications. The resulting optimization problem is nonlinear and nonconvex. Hence, the original plant friendly input design problem is relaxed which results in a convex optimization problem. We formulate a SemiDefinite Programme using the theory of generalized Tchebysheff inequalities to derive tight bounds on the quality of relaxation. Simulations show that the relaxation results in more plant friendly input signals.
IEEE Transactions on Automatic Control 07/2011; · 2.11 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Nearly 20–30% of all process control loops oscillate due to stiction resulting in productivity losses. Thus, detection and quantification of stiction in control valves using routine operating data is an important component of any automated controller performance monitoring application. Many techniques have been proposed for the detection and quantification of stiction. However, most of the approaches assume that the underlying process is linear; very little work is available for nonlinear processes. In this paper, Volterra model-based technique is investigated for the detection of stiction in closed-loop nonlinear systems. The advantages of the proposed method are: (i) it can be used to detect stiction in nonlinear systems and (ii) requires no prior information on whether the loop is linear or nonlinear. Results obtained from simulation and industrial case studies demonstrate the utility of the proposed methodology.
Computers & Chemical Engineering. 01/2010;
-
[show abstract]
[hide abstract]
ABSTRACT: Solid oxide fuel cells (SOFCs) are high temperature fuel cells with a strong potential for stationary power house applications. However, considerable challenges are to be overcome to connect these cells to the power grid. The cells have to satisfy the changing demand of the grid without sacrificing their efficiencies and without causing any structural or material damage. Such an operation, coupled with fast and highly nonlinear transients of the transport variables, leads to a very challenging control problem. This requires an efficient and robust controller. For synthesizing such a controller, a well-validated dynamic model is essential. In this work, a dynamic model is validated by using experimental data from an industrial cell. The data are generated over a broad range of cell temperatures, reactant flow rates, DC polarizations, and amplitudes of step. In the process of validation, it is identified that the Knudsen diffusion and an extended active area for the electrochemical reactions play key roles in determining the current transients of the cell. The dynamic model is used for identification of reduced order models that can be solved in real time for implementation in the MPC framework. Several linear and nonlinear models are considered and the best model is chosen according to the AIC values of the models. Both SISO and MIMO models are identified. For the MIMO model, voltage and H<sub>2</sub> flow are considered as inputs. Power and utilization factors are considered as outputs. A linear model such as ARX model is found to be satisfactory for most SISO cases. However, a nonlinear model such as NAARX model with more cross terms is found to improve the model performance significantly for the MIMO case. All through this work, efforts have been made to synthesize the simplest, yet representative model that can be used for real-time applications.
American Control Conference, 2009. ACC '09.; 07/2009
-
[show abstract]
[hide abstract]
ABSTRACT: In optimal input design problems, the designer seeks to solve for maximally informative inputs to be used as perturbation signals in system identification experiments. Plant- friendly identification experiments are those that satisfy plant or operator constraints on experiment time, input and output amplitudes or input move sizes. These have been reported to be in direct conflict with requirements for good identification. Hence plant-friendly input design is inherently multi-objective in nature. In this contribution, we present the use of two well known techniques of multi-objective optimization to solve for a plant friendly input design where the plant friendly objective is to keep input move sizes low. We relax the constraint on the input move sizes by constraining the variance of the move size instead. Both techniques result in convex optimization problems which can be solved efficiently using powerful algorithms.
American Control Conference, 2008; 07/2008
-
[show abstract]
[hide abstract]
ABSTRACT: Stiction has been reported as the most commonly occurring nonlinearity in control valves. In the literature, mechanistic and data based models have been proposed to characterize stiction. In this paper, the available models are critically analyzed. The complexities associated with modeling stiction are highlighted. It is shown through experiments on industrial valves that in the presence of static and dynamic friction, the valve behavior is dependent on the rate of the valve input. An approach to model this rate dependent valve behavior - which is not considered in existing data driven models - is proposed.
American Control Conference, 2008; 07/2008
-
[show abstract]
[hide abstract]
ABSTRACT: A two-dimensional steady state model for a PEM fuel cell cathode is described in this work. All the components in the cathode such as the gas manifold, diffusion layer, microporous layer and the catalyst layer are modeled. The effect of the liquid water is taken into account in every layer of the cathode. The model was developed and simulated using a combination of Maple and MATLAB. The combination provides a flexible framework for quickly developing models with various assumptions and different complexities. The cathode catalyst layer was modeled using both macrohomogeneous and spherical agglomerate characterizations. The model is validated using experimental data. During model validation, various assumptions are considered for transport within the porous layers of the cathode. Subsequently, the assumptions and characteristics that best predicts the experimental data are highlighted. The major conclusion of this work is that a model that includes liquid water in all the layers with a flooded spherical agglomerate characterization for the reaction layer best predicts the PEM fuel cell behavior in terms of an i–v characterization for a wide range of reactant flow rates. The utility of the steady state model for the optimization of the cathode catalyst layer design parameters is also described.
Journal of Power Sources.
-
[show abstract]
[hide abstract]
ABSTRACT: There has been growing interest in the modeling of proton exchange membrane fuel cells (PEMFC) over the last two decades. While a variety of steady-state models have been proposed, literature is scarce in PEMFC dynamic models and transient studies. Typical dynamic models for PEM fuel cell are empirical current–voltage relationships. The internal transients associated with reactant and product species and other components are usually neglected. A detailed dynamic model for spherical agglomerate in PEM fuel cell is presented in this work. The dynamic model includes detailed mathematical equations for conservation of oxygen and hydrogen ions inside the agglomerate. The agglomerate dynamic model is simulated for typical operating conditions inside the PEMFC catalyst layer. Simulation studies show that the time scales in which the dynamics of agglomerate potential and concentration of dissolved oxygen respond differ by several orders of magnitude. Transient response of agglomerate current to step changes in surface boundary conditions are also presented. Reasons for the typical characteristics observed in the dynamic behavior of agglomerate current are also highlighted.
Journal of Power Sources.
-
[show abstract]
[hide abstract]
ABSTRACT: A two-dimensional two-phase steady state model of the cathode of a polymer electrolyte membrane fuel cell (PEMFC) is developed using unsaturated flow theory (UFT). A gas flow field, a gas diffusion layer (GDL), a microporous layers (MPL), a finite catalyst layer (CL), and a polymer membrane constitute the model domain. The flow of liquid water in the cathode flow channel is assumed to take place in the form of a mist. The CL is modeled using flooded spherical agglomerate characterization. Liquid water is considered in all the porous layers. For liquid water transport in the membrane, electro-osmotic drag and back diffusion are considered to be the dominating mechanisms. The void fraction in the CL is expressed in terms of practically achievable design parameters such as platinum loading, Nafion loading, CL thickness, and fraction of platinum on carbon. A number of sensitivity studies are conducted with the developed model. The optimum operating temperature of the cell is found to be 80–85 °C. The optimum porosity of the GDL for this cell is in the range of 0.7–0.8. A study by varying the design parameters of the CL shows that the cell performs better with 0.3–0.35 mg cm−2 of platinum and 25–30 wt% of ionomer loading at high current densities. The sensitivity study shows that a multi-variable optimization study can significantly improve the cell performance. Numerical simulations are performed to study the dependence of capillary pressure on liquid saturation using various correlations. The impact of the interface saturation on the cell performance is studied. Under certain operating conditions and for certain combination of materials in the GDL and CL, it is found that the presence of a MPL can deteriorate the performance especially at high current density.
Journal of Power Sources.
-
[show abstract]
[hide abstract]
ABSTRACT: Electrochemical systems differ significantly from conventional chemical systems. The response of voltage to changes in current and that of current to changes in voltage is much faster compared to typical transients observed in transport variables. In this work, the transient characteristics of various transport and electrochemical phenomena are studied in the PEM fuel cell cathode using a dynamic model. Model-based chronoamperometry and chronopotentiometry studies are performed to investigate the interactions among the various phenomena and the limiting mechanisms under various operating modes. The dynamic response of current to changes in voltage under chronoamperometry and that of voltage to changes in current under chronopotentiometry are found to be significantly different. Moreover, it is also observed through simulations that the dynamics in the output variables are strongly influenced by the operating cell voltage. Results from chronoamperometry studies are used to highlight the problem of oxygen starvation, which is also reflected by the magnitude of oxygen excess ratio or stoichiometric ratio. Results from step tests in chronopotentiometry studies are used to study nonlinearities in the response of voltage to changes in inputs such as, current and air flow rate.
Chemical Engineering Science.
