The integration of process design control – Summary future directions

Panos Seferlisa; Michael C. Georgiadisb    a CERTH - Chemical Process Engineering Research Institute (CPERI), P.O. Box 361, 57001 Thermi - Thessaloniki, Greece
b Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK

1 Introduction

The integration of process design and control aims at identifying design decisions that would potentially generate and inherit possible trouble to the dynamic performance of the control system. Furthermore, it aims at exploiting the synergistic powers of a simultaneous approach to ensure the economical and smooth operation of the plant despite the influence of disturbances and the existence of uncertainty.

An integrated design methodology requires that a good qualitative and quantitative description of those process characteristics that have a dominant effect on the dynamic behaviour of the process is obtained and their relationship to design decisions is understood. Section 2 summarizes the book chapters on those two directions. The success of the integrated design and control procedure relies on the accurate definition of the problem within a mathematical framework that will assist on the selection of the best possible option from a pool of alternative designs. Section 3 discusses recent advances in methods towards a holistic approach to process design and control. Undoubtedly, the consideration of the unit-to-unit interactions in a flowsheet through recycle streams and feedback control is important for the design of a well-functioning and effective mechanism that ensures the alleviation of exogeneous variations from the final product quality. Section 4 summarises the chapters referring to plantwide control systems design. The frontiers for the integrated process design and control technology are expanding as the need for further integration of an industrial environment of perpetual change and uncertainty grows constantly. Section 5 covers a sample of issues that embrace the ideas of integration in fields of operations, quality assurance, numerical optimisation, scheduling, and batch-wise applications. Finally, an attempt to speculate on future research directions in the field of integrated design and control is taken in Section 6.

2 Process Characterization and Controllability Analysis

Bill Luyben in Chapter A1 provides an excellent introduction to the real need for a simultaneous process and control system design education. The chapter offers a number of illustrative and motivating examples that show in the most vivid and convincing way the advantages of considering steady state economics together with the dynamic performance of the control system when designing new processes. Assuring good and acceptable operation of the plant that is undisputed essential for the overall economic performance should be the main objective in the mind of the design engineer. However, the basic recipe for success relies on the in-depth understanding of the process system and its inherited implications to maintain quality and specifications within acceptable limits in a constantly varying environment.

The research groups of Doyle and Ogunnaike in Chapter A2 provide a comprehensive overview of the key process characteristics that determine to a great extent the selection of the most suitable control system for a given process. The classification of process systems is made based on the degree of process nonlinearity (i.e. deviation from linearity), the dynamic character (i.e. complexity of dynamic behaviour) and degree of interaction (i.e. degree of coupling among controlled and manipulated variables). All possible combinations between the key characteristics each one divided in three levels of intensity are represented in the "process characterization cube". The search for the "joint metric" that fully defines the process character is originated in the investigation of the equivalences between the metrics for individual characteristics. Each combination of properties is indicative of the difficulty to control and operate the process under real operating conditions and is associated to an appropriate set of controller types. Model-order reduction issues pertaining to model-based control design and always in conjunction with the dynamic character of the process are further investigated.

Schweickhardt and Allgöwer in Chapter A3 mainly concentrate on the nonlinearity assessment of processes. A comprehensive overview of general nonlinearity measures and a thorough investigation of the predictive and computational dimension of open loop measures are presented. As the main objective becomes the development of a tool to judge whether a nonlinear controller should be beneficial or needed for a particular process with specific nonlinear characteristics, the controller relevant nonlinearity is quantified. The selected measure is based on the relative differences between the output of nonlinear state feedback law and that of an equivalent linear state feedback law. The controller relevant nonlinearity measure depends not only on the plant dynamics and region of operation but also on the performance criterion used in the derivation of the controller law.

Georgakis and co-workers in Chapter A4 cover the issue of process operability analysis. Operability measures quantify the ability of the process to maintain the operating specifications despite the influence of disturbances in an acceptable dynamic fashion. The analysis is carried out using static and dynamic process models and irrespectively of the selected feedback control structure. Steady state operability defines the percentage of the desired output space that can be achieved by the available input space. Dynamic operability investigates the ability of the design to alleviate the effect of disturbances or reach a new set point level in a timely manner. Thus, the comparison of alternative design decisions based on the static and dynamic operability performance becomes substantially more effective and reliable.

Knowledge of the structure of dynamic modes of a system is undoubtedly useful in process design because it can act as the instrument to manipulate the dynamic properties of a new system. Cameron and Walsh in Chapter A5 explore the spectral association properties of process systems through the association of a group of eigenvalues to a group of process states and a specific dynamic mode. Such behaviour arises due to strong coupling among the states of the system. Different spectral resolution techniques are compared on the basis of computational efficiency and power of analysis in terms of eigenvalue sensitivity, interaction between fast and slow modes and strength of coupling.

An alternative way to investigate the controllability properties of a system is through non-equilibrium thermodynamics. Meeuse and Grievink in Chapter A6 combine process synthesis, non-equilibrium thermodynamics and systems theory to perform the thermodynamic controllability assessment (TCA) of alternative designs. Non-equilibrium thermodynamics describe entropy production as a function of the transferred flux and the respective driving force. The link between process design and thermodynamic description of the process lies within the notion of passivity. The assessment focuses on the design's influence on the entropy production as it is closely related to the control performance. The prediction of disturbance rejection properties for the TCA has been demonstrated through applications in heat transfer and separation processes.

Bogle and co-workers in Chapter A7 provide a critical assessment of the ability of existing and commonly used controllability measures to describe the interactions between design and control for nonlinear problems. A limiting factor is the difficulty to develop generic methods for all types of nonlinear problems. Dynamic simulations and performance metrics are used for the evaluation of alternative designs in an attempt to remove non-minimum phase characteristics. An algorithm for the elimination of input multiplicity, a common source of significant problems in nonlinear systems, is presented. Design modifications based on the best utilization of exergy, the useful energy in a process, result in significant dynamic and control improvements.

3 Integrated Process Design and Control – Methods

A unified framework for the integrated process and control system design involves the determination of a large set of decisions that are linked to the process topology, equipment design specifications, operating conditions, control structure configuration and controller tuning. The design decisions represented as continuous and discrete variables are determined through the optimisation of a set of objective functions that capture the goals and desired properties subject to the static and dynamic behaviour for the system under the presence of both time-varying disturbances and time-invariant uncertainty. The complexity of the design problem thus results mostly in a computationally intensive and challenging solution procedure. The solution is generally facilitated using ingenious approximations and creative simplifications that aim to remove some of the computational burden without significant compromising on the objectives and scope of the design procedure.

Pistikopoulos and co-workers in Chapter B1 provide a holistic approach that relies on novel multi-period mixed integer...