F.Y. Wang

Review and future directions in the modelling and control of continuous drum granulation

Many granulation plants operate well below design capacity, suffering from high recycle rates and even periodic instabilities. This behaviour cannot be fully predicted using the present models. The main objective of the paper is to provide an overview of the current status of model development for granulation processes and suggest future directions for research and development. The end-use of the models is focused on the optimal design and control of granulation plants using the improved predictions of process dynamics. The development of novel models involving mechanistically based structural switching methods is proposed in the paper. A number of guidelines are proposed for the selection of control relevant model structures.

A generalised dynamic model for char particle gasification with structure evolution and peripheral fragmentation

A generalised model for the prediction of single char particle gasification dynamics, accounting for multi-component mass transfer with chemical reaction, heat transfer, as well as structure evolution and peripheral fragmentation is developed in this paper. Maxwell-Stefan analysis is uniquely applied to both micro and macropores within the framework of the dusty-gas model to account for the bidisperse nature of the char, which differs significantly from the conventional models that are based on a single pore type. The peripheral fragmentation and random-pore correlation incorporated into the model enable prediction of structure/reactivity relationships. The occurrence of chemical reaction within the boundary layer reported by Biggs and Agarwal (Chem. Eng. Sci. 52 (1997) 941) has been confirmed through an analysis of CO/CO2 product ratio obtained from model simulations. However, it is also quantitatively observed that the significance of boundary layer reaction reduces notably with the reduction of oxygen concentration in the flue gas, operational pressure and film thickness. Computations have also shown that in the presence of diffusional gradients peripheral fragmentation occurs in the early stages on the surface, after which conversion quickens significantly due to small particle size. Results of the early commencement of peripheral fragmentation at relatively low overall conversion obtained from a large number of simulations agree well with experimental observations reported by Feng and Bhatia (Energy & Fuels 14 (2000) 297). Comprehensive analysis of simulation results is carried out based on well accepted physical principles to rationalise model prediction

Dynamic simulation of bioreactor systems using orthogonal collocation on finite elements

Abstract The dynamics of continuous biological processes is addressed in this paper. Numerical simulation of a conventional activated sludge process shows that despite the large differences in the dynamics of the species investigated. the orthogonal collocation on finite element technique with three internal collocation and four elements (OCFE-34) gives excellent numerical results for bioreactor models up to a Peclet number of 50. It is shown that there is little improvement in numerical accuracy when a much larger internal collocation point is introduced. Over and above Peclet number of 50, considered to be large for this process. simulation with the global orthogonal collocation (GOC) technique is infeasible. Due to the banded nature of its structural matrix, the method of lines (MOL) technique requires the lowest computing time, typically four times less than that required by the OCFE-34. Validation of the hydraulics of an existing pilot-scale subsurface flow (SSF) constructed wetland process using the aforementioned numerical techniques suggested that the OCFE is superior to the MOL and GOC in terms of numerical stability.

A SIMPLE DYNAMIC MODEL FOR SOLID TRANSPORT IN ROTARY DRYERS

ABSTRACT The solid particle movement in a rotary drum plays an important role in drying processes. The solid distribution in the drum affects the amount of contact surface between the solid and the gas. The retention time of solids influences the time particles can stay in contact with the gas in order to transfer heat and mass. Any heat and mass transfer model for a solid particle dryer must be able to predict solid flowrate and solid hold-up. There have been several reports in the literature regarding the modelling aspects of solid transport in dryers. If the model is developed for model-based control, it must be simple and yet represent dynamics of the system accurately. This paper addresses solid motion modelling and the effects of different variables involved in solid transport phenomena. Sugar drying process is the case study in this work. A steady state semi-empirical model was modified to predict solid hold-up and flowrate in rotary dryers. This model was incorporated into a heat and mass transfer model ;o predict solid moisture and temperature for inferential and model-based control purposes. Results of several experiments that have been used to investigate dynamics of the system in terms of solid motion and to validate the model are also presented. The approach advocated in this paper is directly applicable to the transport of other solids in rotary drum equipment and can thus be regarded as a generalized model.

Control studies on a model evaporation process - constrained state driving with conventional and higher relative degree systems

A number of state driving strategies are investigated for a model evaporation process described by three different sets of state equations. These include optimal and model-based non-linear approaches. A structural analysis shows that with varied mathematical assumptions, the mathematical models of the evaporation process can be classified into different control classes. Conditions for steady state optimality of the systems are firstly determined by employing a standard nonlinear programming technique. Optimal control in the presence of both control and state constraints is then studied by using Pontryagins maximum principle and a control parameterization approach for obtaining time optimal trajectories. Comprehensive comparative studies are carried out between: (1) optimal control strategies and nonlinear model based control algorithms: (2) constrained and unconstrained GMC algorithms; and (3) different modelling strategies. The development of different models in control studies is significant, due to a variety of important issues including control loop interaction, centralized and decentralized control schemes, relative degree (RD) and output controllability. These issues are investigated by employing concepts from a differential geometrical approach (DGA). Two methods to handle higher RD systems with GMC algorithms are proposed. Physical explanations for the general characteristics of the observed trajectories are presented. It is shown that the evaporator models stated in this work provide good case study examples for investigating the behaviour of control systems with an ill-conditioned decoupling matrix or a higher relative degree. The importance of appreciating optimal control issues in designing and operating evaporation processes is emphasized.

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.

Evaluation of control strategies for fertiliser granulation circuits using dynamic simulation

A control strategy for fertiliser granulation circuits is developed by employing a dynamic model which is based on a sound understanding of granulation mechanisms. The overall study of the control strategies includes selection of the controlled variables, determination of the control structure and case studies. Recycle size distribution is chosen as an easily measured controlled variable and a PI controller is implemented in the process. An examination for the control of a di-ammonium phosphate granulation process is carried out by using the NIMBUS Simulator. The simulation results show the off-set of the granule mean size and the moisture content caused by the step change disturbance is reduced greatly compared with the open loop simulation. The issues for the control of the large time lag and the large recycle stream are discussed.

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications

Dynamic modelling and simulation of activated sludge process using orthogonal collocation approach

This paper deals with the improvement in modelling of the dynamics of activated sludge wastewater treatment process using a distributed parameter approach. A computational algorithm, based on the global orthogonal collocation technique, for the activated sludge process is developed in this work. Steady-state and dynamic simulations are performed based on this algorithm. The system configuration considers backmixing or intermixing, which can represent the actual process more accurately than the idealised flow schemes commonly employed for the design and modelling of the activated sludge reactors. Based on a dispersed plug flow model for activated sludge bioreactor formulated in this work, a Peclet number in the order of 0.5 to 5 and 5 to 7 internal collocation points are recommended for modelling channel-type activated sludge bioreactor. The dynamics of substrate is predicted well whereas the prediction for biomass is fair, when compared to the experimental data. It is also demonstrated in this paper that the proposed algorithm can give superior prediction of process dynamics than the commonly-used tanks-in-series technique. Dynamic responses caused by disturbances in the influent wastewater which propagates at various spatial positions along the bioreactor can be correctly predicted through simulations.

The wavelet-collocation method for transient problems with steep gradients

A numerical procedure based on wavelet collocation is suggested and developed for the solution of models for packed-bed chemical reactors and chromatographic columns. The wavelet collocation approach converts problems to the solution of a system of algebraic and differential equations for the unknown wavelet series coefficients. Induced matrices are sparce and can accelerate integration even when the number of differential equations is large. Wavelets have the capability of representing solutions at different levels of resolution making them useful for developing hierarchical solutions for chemical process.