Terminal composition control of a binary distillation column

Wood, R. K.; Berry, Matthew

doi:10.1016/0009-2509(73)80025-9

Cited by 633 publications

(279 citation statements)

References 5 publications

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“…The distillation column benchmark problem [31] is studied here. The system has two inputs and two outputs, and the system dynamics is represented by the following transfer function matrix.…”

Section: Resultsmentioning

confidence: 99%

Modified active disturbance rejection control for time-delay systems

2014

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Section: Resultsmentioning

confidence: 99%

Modified active disturbance rejection control for time-delay systems

2014

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“…For multiple variable processes, the performance of each algorithm is compared with Wood and Berry distillation column control [14]. The control strategy for multivariable system is presented by Wood and Berry, which is to reduce the interaction between the control of the overhead and bottom products [14].…”

Section: Application On Mimo Optimizationmentioning

confidence: 99%

“…The control strategy for multivariable system is presented by Wood and Berry, which is to reduce the interaction between the control of the overhead and bottom products [14]. Figure 4b shows the MIMO control structure designed for this work.…”

Section: Application On Mimo Optimizationmentioning

confidence: 99%

Single and Multiple variables control using Tree Physiology Optimization

Halim

Ismail

2017

MATEC Web Conf.

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Abstract. This paper presents the tuning of single-input single-output (SISO), and multiple-input multiple-output (MIMO) control system using Tree Physiology Optimization (TPO). TPO is a metaheuristic optimization algorithm that has a clustered diversification search strategy inspired from plant shoots growth. The clustered diversification is referred as tree branch and leaves. The exploration is amplified from roots growth counterparts. In the proposed method, each shoot from each branch search for possible solution in parallel and the fitness is evaluated based on all best values found by branch search. The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). Results shown that TPO is able to find good PID parameters with lesser settling time for SISO and MIMO process. NMS is also able to find good PID parameters for SISO with lesser performance index, however not able to find better solution in MIMO control. PSO converged prematurely in SISO control and has high overshoot for MIMO control optimization.

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“…Each such element is modelled in FOLPD form; Wood and Berry [41], for example, develop a 2x2 MIMO model of this form for a distillation column. In a simulation, the MIMO process model from 0 to 300 sample periods, and from 300 to 600 sample periods is, respectively, The elements of the MIMO process model terms are the discrete time equivalents of FOLPD continuous-time transfer functions.…”

Section: Mimo Process Model -Time Delay Is An Integer Multiple Of Thementioning

confidence: 99%

Identification of a time-delayed process model using an overparameterisation method

Roe¹,

Gao²,

O’Dwyer³

2007

China-Ireland International Conference on Information and Communications Technologies (CIICT 2007)

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This paper briefly reviews the main overparameterisation methods for the Single-Input, Single Output (SISO) and Multi-Input, Multi-Output (MIMO) model parameter (and time delay) estimation problem. Subsequently, two algorithms, and their modifications, are discussed, and their performances are assessed in simulation. Results indicate that both the algorithms can suitably identify the model parameters, including the time delay. The third author has taught the method successfully to students taking advanced level control courses at DIT for a number of years; these experiences will be briefly reported. The paper also discusses the advantages and disadvantages of the overparameterisation approach.

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Terminal composition control of a binary distillation column

Cited by 633 publications

References 5 publications

Modified active disturbance rejection control for time-delay systems

Modified active disturbance rejection control for time-delay systems

Single and Multiple variables control using Tree Physiology Optimization

Identification of a time-delayed process model using an overparameterisation method

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