Parisa A. Bahri

Estimating Average Particle Size by Focused Beam Reflectance Measurement (FBRM)

The Lasentec focused beam reflectance measurement (FBRM) probe provides in situ particle characterisation over a wide range of suspension concentrations. This is a significant advantage over conventional instruments that require sampling and dilution. However, FBRM gives a chord distribution, rather than a conventional diameter distribution. Both theoretical and empirical methods for converting from chord to diameter data are available, but the empirical method was found to be more successful. The FBRM response has been compared to conventional particle sizing techniques (laser diffraction and electrical sensing zone) for a range of sieved aluminium or calcite suspensions. The mode average of the square-weighted chord length was found to be comparable to other sizing techniques over the range from 50 to 400 μm. The square-weighted FBRM results were essentially unaffected by changes to the instrument focal position, the suspension fluid flow velocity, or the solid fraction in the range 0.1-20% w/v.

A survey of Petri net applications in batch processes

Batch processes are fundamentally different from continuous chemical processes in both their design and operations, which pose a diversity of problems to system engineering and process control. As an emerging methodology for batch processes, Petri net has found its applications in different aspects of modelling, qualitative and quantitative analysis, supervisory and coordinate control, planning and scheduling, and hybrid system design. In this paper, recent research on Petri net applications in batch processes is presented, and future directions are discussed.

Economic impact of disturbances and uncertain parameters in chemical processes—A dynamic back-off analysis

Abstract Optimal operating conditions in chemical plants are characterized by operation on a number of active constraints. The presence of disturbances and model uncertainties can easily cause constraint violations. Thus, it is necessary to move the operating point away from the active constraints into the feasible region (back-off). Recently a strategy for detemining the necessary open-loop steady-state back-off from the nominal optimum has been developed by the authors, which consists of solving a joint steady-state optimization-flexibility problem. This paper extends these ideas to consider dynamic situations, thus leading to a joint dynamic optimization-flexibility problem. Having determined the economic penalty associated with open-loop back-off in dynamic systems, the next step is to estimate the potential recovery of this penalty that various control schemes might provide. The proposed approach also includes the optimization of the controller parameters. Results are given for a simple flowsheet example.

Petri-net based formulation and algorithm for short-term scheduling of batch plants

Effective scheduling of operations in batch plants has a great potential for high economic returns, in which the formulation and optimal solution algorithm are the main issues of study. Petri-nets have proven to be a promising technique to solve many difficult problems associated with the modeling, formal analysis, design and coordination control of discrete event systems. One of the major advantages of using a Petri-net model is that the same model can be used for the analysis of behavioral properties and performance evaluation, as well as for the systematic construction of discrete event simulators and controllers. This paper aims to present a Petri-net based approach for the scheduling of operations in batch plants. Firstly, the short-term scheduling of batch plants is formulated using timed Petri-net. Secondly, the heuristic search algorithm for scheduling of batch plants is given, which is based on generating and checking the markings in the reachability tree of the Petri-net model. Finally, the novel formulation and algorithm are tested using two simulation case studies, and compared against traditional methods.

Integration techniques in intelligent operational management: a review

Until recently the concept of an integrated framework for coordinating operational tasks in industrial plants has not been possible due to technological limitations. Integration of functions within an intelligent system architecture would result in improved plant performance, safety and an increase in production. As a result of increased computing power and powerful memory systems, a fully computer integrated system is now possible, however, achieving an integrated framework for operational tasks is quite complex. Problems of task integration include not only the consideration of information flow and timing for a continuously changing environment, but the integration of various problem-solving methodologies. Integration frameworks proposed in the past fail to provide for a fully integrated system. A new approach to accommodate the changing dynamics of a plants operation is now possible with the Coordinated Knowledge Management method. This paper reviews the components that need to be integrated to encompass intelligent process operation. It also reviews various integration frameworks outlining limitations and presents a proposed method of integration based on knowledge management.

A two-step supervisory fault diagnosis framework

Techniques enabling early detection and diagnosis of faults are important in the processing industries. This paper emphasises a technique for early fault detection and diagnosis based on dynamic fault data and a two-step fault detection and diagnosis framework. The approach shows various advantages over alternative methods including prompt fault detection and localisation, applicability to large-scale systems without the need for excessive computing resources, and a modular architecture that allows plant sections to be treated individually. In the proposed method, the large-scale plant is broken up into sections and a Petri net based on real time data is used to locate the particular section of the plant in which the fault originates. This Petri net then activates secondary neural networks, which diagnose the exact location of the fault in that particular plant section. Applicability of the proposed technique is demonstrated through a pilot plant case study.

A multiple model, state feedback strategy for robust control of non-linear processes

The major limitation of reported multiple model approaches is that robustness against process/controller disturbances cannot be addressed for processes consisting of hybrid stable/unstable regimes, or with chaotic dynamics. In this paper, a significantly modified multiple model approach is developed to achieve robust control with global stability. The new advances include: (1) stabilization of open-loop unstable plants using a state feedback strategy, (2) incorporation of an adjustable pre-filter to achieve offset-free control, (3) implementation of a Kalman filter for state estimation, and (4) connection of the multiple model approach with non-linear model predictive control to achieve a precise control objective. The improved controller design method is successfully applied to two non-linear processes with different chaotic behaviour. Compared with conventional methods without model modifications, the new approach has achieved significant improvement in control performance and robustness with a dramatically reduced number of local models.

Hybrid intelligent scenario generator for business strategic planning by using ANFIS

The aim of this study is to investigate a new method for generating scenarios in order to cope with the data shortage and linguistic expression of experts in scenario planning. The proposed hybrid intelligent scenario generator uses an Adaptive Neuro-Fuzzy Inference System (ANFIS) to deal with uncertain inputs. In this methodology, the strengths of expert systems, fuzzy logic and Artificial Neural Networks (ANNs) are joined to generate possible future scenarios. The proposed methodology includes four steps: step 1 defines the scope and internal and external variables and step 2 determines rules from experts. Then, step 3 prepares ANFIS system which is conducted by computer programming in Matlab environment. The Last step is sensitivity analysis to study the effects of variation of inputs on outputs. The applicability of the proposed method has been tested against two different case studies.

An integrated Petri net and GA based approach for scheduling of hybrid plants

Production scheduling in mixed batch/continuous plants, due to their hybrid nature, can become very complex. The main contribution of this paper is the presentation of a novel approach based on the integration of the Timed arc hybrid Petri net (TAHPN) and a genetic algorithm (GA) as a suitable tool for scheduling of hybrid systems. The major benefit of this approach is a significant reduction in complexity during problem formulation. The proposed method is explained through a sugar mill case study.

Back-off calculations in optimising control: A dynamic approach

The ultimate goal in the operation of chemical plants is to work at the possible optimal conditions. However, most of the time, a plant is faced with uncertain conditions during its operation. To efficiently handle these uncertainties, chemical plants must have the flexibility to achieve feasible operation over a range of uncertain conditions. One way to accomplish this, is by moving the nominal optimum to some permanently feasible operating point inside the feasible region (back-off point). In a previous study (Bahri et al., 1994), an iterative approach to solve this problem at steady-state has been proposed (Steady State Open-Loop Back- Off Calculation). In order to consider the transient behaviour of a system responding to disturbances, the back-off calculation should be based upon a dynamic model of the system. Having determined the economic penalty associated with the dynamic open-loop back-off, the next step is to estimate the potential recovery that various control schemes of varying complexity might provide. The methodology to solve the Dynamic Back-Off problem and a flowsheet example are presented in this paper.