Effect of disturbance directions on closed-loop performance

Skogestad, Sigurd; Morari, Manfred

doi:10.1021/ie00070a017

Cited by 115 publications

(56 citation statements)

References 5 publications

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“…Model uncertainties Skogestad and Morari (1987) studied the effects of model uncertainties on control performances. Uncertainties in the process model require that the actual controller be detuned and hence degrade the control performance.…”

Section: 324mentioning

confidence: 99%

Integration of process design and control: A review

Sharifzadeh

2013

Chemical Engineering Research and Design

115

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There is a large variety of methods in literature for process design and control, which can be classified into two main categories. The methods in the first category have a sequential approach in which, the control system is designed, only after the details of process design are decided. However, when process design is fixed, there is little room left for improving the control performance. Recognizing the interactions between process design and control, the methods in the second category integrate some control aspects into process design. With the aim of providing an exploration map and identifying the potential areas of further contributions, this paper presents a thematic review of the methods for integration of process design and control. The evolution paths of these methods are described and the advantages and disadvantages of each method are explained. The paper concludes with suggestions for future research activities. KeywordsIntegrated design and control, Sequential design and control, Control structure selection, Simultaneous optimization of a process and its controllers, inversely controlled process model, controllability.

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Section: 324mentioning

confidence: 99%

Integration of process design and control: A review

Sharifzadeh

2013

Chemical Engineering Research and Design

115

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“…For that, (P) should have been computed for all IO sets of that dimension. Skogestad and Morari (1987a) consider the disturbance condition number. For the kth disturbance d I in Fig.…”

Section: The Condition Numbermentioning

confidence: 99%

A review of methods for input/output selection

2001

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Control system design involves input/output (IO) selection, that is, decisions on the number, the place, and the type of actuators and sensors. The choice of inputs and outputs a!ects the performance, complexity, and costs of the control system. Due to the combinatorial nature of the selection problem, systematic methods are needed to complement one's intuition, experience, and physical insight. This paper reviews the currently known IO selection methods, which aids the control engineer in picking a suitable method for the problem at hand. The methods are grouped according to the control system property that is addressed and applications are grouped according to the considered control systems. A set of criteria is proposed that a good IO selection method should possess. It is used to assess and compare the methods and it could be used as a guideline for new methods. The state of the art in IO selection is sketched and directions for further research are mentioned.

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“…The scaling used for condition number calculations depends on whether it is being used for manipulated constraint assessment or for uncertainty assessment. Johnston and Barton (1987) and Skogestad and Moran (1987) recommend scalings for manipulated constraint analysis. Perkins and Wong (1985) and Moran and Skogestad (1985) suggest scalings to minimise the condition number for robustness analysis.…”

Section: Controllability Analysismentioning

confidence: 99%

Selection of process control structure based on economics

Narraway¹,

Perkins²

1994

Computers & Chemical Engineering

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It has been recognised that the effect of dynamics on process economics is heavily dependent on the implemented controller, and that the physically attainable controller performance is limited by the choice of controlled and manipulated variables. This work considers the systematic selection of economically optimal square regulatory control structures from the set of all possible measurements and manipulated variables. This is a combinatorial problem, as typical processes have millions of potential control structures, where a control structure consists of a set of variables to be controlled and manipulated, but does not include a control law relating the variables.The solution of such a synthesis problem requires an analysis method. Historical approaches to control structure evaluation consider "controllability indices", and their trade off against steady state economics, whereas the economic indicators described in this thesis allow direct comparison and trade off of control structures against steady state economics.Assuming a method for assessing control structure economics, a hierarchical decomposition of the design problem into steady state and dynamic problems is demonstrated.A method for assessing the effect of dynamics on process economics for a specific control structure without tuning a controller is developed, based on linearised process models, linear systems theory and constraint control concepts. This assessment is extended to consider the control structure selection problem, resulting in a mixed integer linear programming (MILP) outer approximation to a mixed integer nonlinear programming (MINLP) problem.A mixed integer nonlinear optimal control problem is posed for the problem of selecting an optimal multiloop proportional-integral process control structure.The above problems are formulated as standard optimisation problems, and solved by appropriate techniques. Experience with the methods is presented as a set of case studies.Finally the novel features and applications of the work are discussed along with potential areas of further research.

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Effect of disturbance directions on closed-loop performance

Cited by 115 publications

References 5 publications

Integration of process design and control: A review

Integration of process design and control: A review

A review of methods for input/output selection

Selection of process control structure based on economics

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