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Abstract
This thesis describes the development and application of a new systematic modelbased methodology for performing integrated process design and controller design
(IPDC) of chemical processes. The new methodology is simple to apply, easy to visualize and efficient to solve. Here, the IPDC problem that is typically formulated as a mathematical programming (optimization with constraints) problem is solved by the socalled reverse approach by decomposing it into four sequential hierarchical subproblems: (i) preanalysis, (ii) design analysis, (iii) controller design analysis, and (iv) final selection and verification. Using thermodynamic and process insights, a
bounded search space is first identified. This feasible solution space is further reduced to satisfy the process design and controller design constraints in subproblems 2 and 3, respectively, until in the final subproblem all feasible candidates are ordered according to the defined performance criteria (objective function). The final selected design is then verified through rigorous simulation.
In the preanalysis subproblem, the concepts of attainable region and driving force are used to locate the optimal processcontroller design solution in terms of optimal condition of operation from design and control viewpoints. The targets for the designcontrol solution are defined at the maximum point of the attainable region and driving force diagrams. Defining the targets at the maximum point of the attainable region and driving force diagram ensure the optimal solution not only for the process design but also for the controller design. From a process design point of view at these targets, the optimal design objectives can be obtained. Then by using the reverse solution approach, values of designprocess variables that match those targets are calculated in
Stage 2. Using model analysis, controllability issues are incorporated in Stage 3 to calculate the process sensitivity and to pair the identified manipulated variables with the corresponding controlled variables. From a controller design point of view, at targets defined in Stage 1, the sensitivity of controlled variables with respect to disturbances is at the minimum and the sensitivity of controlled variables with respect to manipulated variables is at the maximum. Minimum sensitivity with respect to disturbances means that the controlled variables are less sensitive to the effect of
disturbances and maximum sensitivity with respect to manipulated variables determines the best controller structure. Since the optimization deals with multicriteria
objective functions, therefore, in Stage 4, the objective function is calculated to verify the best (optimal) solution that satisfies design, control and economic
criteria. From an optimization point of view, solution targets at the maximum point of the attainable region and driving force diagrams are shown the higher value of the
objective function, hence the optimal solution for the IPDC problem is verified. While other optimization methods may or may not be able to find the optimal solution,
depending on the performance of their search algorithms and computational demand, this method using the attainable region and driving force concepts is simple and able to find at least nearoptimal designs (if not optimal) to IPDC problems.
The developed methodology has been implemented into a systematic computeraided framework to develop a software called ICASIPDC. The purpose of the software is to
support engineers in solving process design and controller design problems in a systematic and efficient way. The proposed methodology has been tested using a series of case studies that represents three different systems in chemical processes: a single reactor system, a single separator system and a reactorseparatorrecycle system.
Original language  English 

Place of Publication  Kgs. Lyngby, Denmark 

Publisher  Technical University of Denmark 
Number of pages  250 
ISBN (Print)  9788792481399 
Publication status  Published  Mar 2011 
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Dive into the research topics of 'ModelBased Integrated Process Design and Controller Design of Chemical Processes'. Together they form a unique fingerprint.Projects
 1 Finished

Integration of Modelling, Design and Control for Efficient Operation of chemical Processes
Abd Hamid, M. K. B. (PhD Student), Gani, R. (Main Supervisor), Sin, G. (Supervisor), Gernaey, K. V. (Examiner), Manan, Z. A. (Examiner) & Skogestad, S. (Examiner)
01/07/2007 → 13/04/2011
Project: PhD