General tuning procedure for the nonlinear balance-based adaptive controller

Stebel, Krzysztof; Czeczot, Jacek; Laszczyk, Piotr

doi:10.1080/00207179.2013.822103

Cited by 25 publications

(10 citation statements)

References 28 publications

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“…Consequently, it is adjusted as ∞ = P P 0 and remains constant for adjusted α [5]. At the same time, the estimate Y R always tracks its true value compensating inaccuracies of the simplified model (1) [5].…”

Section: F Additional Important Functionalitiesmentioning

confidence: 96%

“…This parameter is estimated on-line on the basis of measurement data to ensure adaptability. The estimation always converges to the true value without any additional process excitation [4,5].…”

Section: Introductionmentioning

confidence: 94%

“…The tunings for the PI controller have been determined on the basis of the step response of the process and adjusted as k C = 11.25 and T I = 40. The tunings for the B-BAController were determined according to the tuning rule [5] . Experimental results of the pH control with bumpless switching and anti-windup action -manipulating variable applied to the system.…”

Section: Implementation For Ph Controlmentioning

confidence: 99%

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Function block practical implementation of Balance-Based Adaptive Control for pH process

Klopot

Stebel

Czeczot

et al. 2013

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

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This paper deals with the Balance-Based Adaptive Control (B-BAC) of the pH process. The implementation is in the form of the general, flexible and ready-to-use function block written for Allen Bradley® PLC family according to IEC-61131-3 standard. Additionally, the very important aspects of practical implementation are addressed: signal conditioning, bumpless switching, anti-windup action, etc. Experimental results show the functionality of this function block and the superiority of the B-BAC methodology over the conventional PI control in the application to the laboratory pH process.

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Section: F Additional Important Functionalitiesmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 94%

Section: Implementation For Ph Controlmentioning

confidence: 99%

See 1 more Smart Citation

Function block practical implementation of Balance-Based Adaptive Control for pH process

Klopot

Stebel

Czeczot

et al. 2013

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society

Self Cite

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show abstract

“…The tuning rule for the B-BAController [13] is based on the similarity between its linear approximation and general PI controller. The values of λ and α are calculated on the previously adjusted PI tunings and on the value of the function g(.)…”

Section: Simulation Experiments and Conclusionmentioning

confidence: 99%

Nonminimum-phase process control with controllers based on simplified modeling

Laszczyk

Czeczot

2012

2012 IEEE International Conference on Control Applications

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This paper deals with the control of the example heating-cooling nonminimum-phase system based on its simplified modeling. Two models are considered: FOPDT (First Order + Dead Time) approximation of the step response and simplified first order physical model. On the basis of these models, two model-based control strategies are derived: Balance-Based Adaptive Controller (B-BAC) and Predictive Functional Controller (PFC). They are implemented as virtual controllers and their control performance is verified by simulation in the presence of significant modeling inaccuracies. The results show the superiority of B-BAC and PFC over conventional PI control.

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“…First, based on the FOPTD model, the parameters of the PI controller are determined. Then, the obtained parameters are used to calculate the controller parameters for the DMC and B-BAC algorithms according to the methods presented in Laszczyk et al, 2013;Stebel et al, 2014). As a result, if there is a new set-point for the plant, the controller parameters can be easily determined by using the new parameters of the FOPTD model.…”

Section: Implementation Of the Metamorphic Controller In The Plcmentioning

confidence: 99%

A metamorphic controller for plant control system design

Klopot¹,

Skupin²,

Choinski³

et al. 2016

MIC

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One of the major problems in the design of industrial control systems is the selection and parameterization of the control algorithm. In practice, the most common solution is the PI (proportional-integral) controller, which is simple to implement, but is not always the best control strategy. The use of more advanced controllers may result in a better efficiency of the control system. However, the implementation of advanced control algorithms is more time-consuming and requires specialized knowledge from control engineers. To overcome these problems and to support control engineers at the controller design stage, the paper describes a tool, i.e., a metamorphic controller with extended functionality, for selection and implementation of the most suitable control algorithm. In comparison to existing solutions, the main advantage of the metamorphic controller is its possibility of changing the control algorithm. In turn, the candidate algorithms can be tested through simulations and the total time needed to perform all simulations can be less than a few minutes, which is less than or comparable to the design time in the concurrent design approach. Moreover, the use of well-known tuning procedures, makes the system easy to understand and operate even by inexperienced control engineers. The application was implemented in the real industrial programmable logic controller (PLC) and tested with linear and nonlinear virtual plants. The obtained simulation results confirm that the change of the control algorithm allows the control objectives to be achieved at lower costs and in less time.

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General tuning procedure for the nonlinear balance-based adaptive controller

Cited by 25 publications

References 28 publications

Function block practical implementation of Balance-Based Adaptive Control for pH process

Function block practical implementation of Balance-Based Adaptive Control for pH process

Nonminimum-phase process control with controllers based on simplified modeling

A metamorphic controller for plant control system design

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