Smith predictor based robust fractional order control: Application to water distribution in a main irrigation canal pool

Feliu-Batlle, Vicente; Rivas-Pérez, Raul; Castillo-García, Fernando J.; Rodríguez, Luis Sánchez

doi:10.1016/j.jprocont.2008.05.004

Cited by 83 publications

(44 citation statements)

References 30 publications

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“…According to [4][5][6][7][8][9], a typical main irrigation canal consists of several pools separated by undershot gates that are used for regulating the water distribution from one pool to the next one. The controlled variables are water levels at the end of the canal pool and the manipulated variables are the gate positions.…”

Section: Main Irrigation Canal Pool -Mathematical Description and Conmentioning

confidence: 99%

“…However, fractional order control has not only theoretical meaning, but it had already influenced also many real control applications. The nice examples of the practical use with direct impact on more effective management of precious water resources were published in [4][5][6][7][8][9], where the main irrigation canals were controller under various conditions. Systems with parametric uncertainty represent common but also effective way of incorporating the uncertainty into mathematical model.…”

Section: Introductionmentioning

confidence: 99%

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Robust Stabilization of a Main Irrigation Canal Pool via Fractional Order PI Controller: A Graphical Investigation

Matušů¹

2016

DAAAM Proceedings

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This contribution is focused on graphical investigation of robust stability for a feedback control loop containing the parametrically uncertain second order time-delay model of a main irrigation canal pool and a fractional order PI controller. The robust stability of the family of fractional order closed-loop characteristic quasipolynomials is analyzed by means of the sampled value sets and application of the zero exclusion condition.

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Section: Main Irrigation Canal Pool -Mathematical Description and Conmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Stabilization of a Main Irrigation Canal Pool via Fractional Order PI Controller: A Graphical Investigation

Matušů¹

2016

DAAAM Proceedings

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“…A good tuning rule should be capable of taking these uncertainties into account while also maintaining the control performance. In order to test the inherent robustness of these optimal PID/FOPID tuning rules simulations are carried out for variation in process dcgain ( ), maximum time constant ( , [52]- [53], time constant [54]- [56] and time delay [57]- [58] and improvement in control performance has also been shown. Similar to the mentioned literatures ±10% variation in dc-gain [52], ±20% variation in dominant time constant [54] and ±50% variation in time-delay [57] has been done with the controller parameters reported in Table 5.…”

Section: Effect Of Plant Perturbation On the Tuning Rulesmentioning

confidence: 99%

Improved model reduction and tuning of fractional-order PIλDμ controllers for analytical rule extraction with genetic programming

et al. 2012

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Abstract:Genetic Algorithm (GA) has been used in this paper for a new approach of sub-optimal model reduction in the Nyquist plane and optimal time domain tuning of PID and fractional order (FO) PI λ D μ controllers. Simulation studies show that the Nyquist based new model reduction technique outperforms the conventional H 2 norm based reduced parameter modeling technique. With the tuned controller parameters and reduced order model parameter data-set, optimum tuning rules have been developed with a test-bench of higher order processes via Genetic Programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by weighted sum of error index and controller effort. From the reported Pareto optimal front of GP based optimal rule extraction technique a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP based tuning rules has been compared with original GA based control performance for the PID and PI λ D μ controllers, handling four different class of representative higher order processes. These rules are very useful for process control engineers as they inherit the power of the GA based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three dimensional plots of the required variation in PID/FOPID controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP based tuning rules has also been shown with credible simulation examples.

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“…In this paper, the fractional order PID controller is used in a Smith predictor scheme to control plants with time delays. In [9] a frequency domain design approach for time delay systems has been proposed. The fractional controller in the Smith predictor structure in [9] is designed to fulfill stability conditions in frequency domain.…”

Section: Introductionmentioning

confidence: 99%

“…The fractional controller in the Smith predictor structure in [9] is designed to fulfill stability conditions in frequency domain. The proposed methodology in [9] has been applied to design controllers for water distribution in a main irrigation canal pool.…”

Section: Introductionmentioning

confidence: 99%

A New Approach to Design Smith Predictor Based Fractional Order Controllers

Khandani¹,

Jalali²

2010

IJCEE

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I. INTRODUCTIONDead times, or time delays, are found in many processes in industry. Dead times are mainly caused by the time required to transport mass, energy or information, but they can also be caused by processing time or by the accumulation of time lags in a number of simple dynamic systems connected in series [1]. Compared to processes without delays, the presence of a delay in the process greatly complicates the analytical aspects of the control system design, making it more difficult to achieve a satisfactory level of control [2]. Time-delay has been a common phenomenon to overcome whenever we close a feedback loop for the purpose of controlling any system. Recent increase of control applications in the variety gives more importance to systematic methods to cope with time delay. In order to compensate the negative effects of time delay, a well-known and highly effective dead-time compensator for stable processes is Smith predictor [3]. In this predictor scheme, a mathematical model of the process is implemented in an internal feedback loop around a conventional controller. The distinctive scheme was proposed by O.J.M.Smith approximately 50 years ago, and is still attracting much attention for its usefulness. The major advantage of the Smith predictor is that delay issues can be ignored when designing the controller.Fractional-order dynamic systems and controllers, which are based on fractional-order calculus have been gaining attention in several research communities since the last few years [4]. A few recent works in this direction as well as

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Smith predictor based robust fractional order control: Application to water distribution in a main irrigation canal pool

Cited by 83 publications

References 30 publications

Robust Stabilization of a Main Irrigation Canal Pool via Fractional Order PI Controller: A Graphical Investigation

Robust Stabilization of a Main Irrigation Canal Pool via Fractional Order PI Controller: A Graphical Investigation

Improved model reduction and tuning of fractional-order PIλDμ controllers for analytical rule extraction with genetic programming

A New Approach to Design Smith Predictor Based Fractional Order Controllers

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