Self-tuning strategy for a minimum variance control system of a highly disturbed process

Filip, Ioan; Vasar, Cristian; Szeidert, Iosif; Proştean, Octavian

doi:10.1016/j.ejcon.2018.06.004

Cited by 11 publications

(26 citation statements)

References 6 publications

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“…The control law design involves minimizing a cost function described by relation (4) [15][16][17][18]:…”

Section: Design Of the Minimum Variance Control Lawmentioning

confidence: 99%

“…Based on the minimization of a cost function described as a sum of two quadratic terms, the goals of the designed control law are the minimization of the controlled output variance, simultaneously with the minimization of the controller output variance (see relation 1, where E is an expectation operator) [15][16][17][18]:…”

Section: Introductionmentioning

confidence: 99%

“…The second mentioned goal (leading to a suboptimal control) is a mandatory condition to ensure the possibility of practical implementation, imposing a penalty on the control variance, so that the computed control values to be physically achievable [15][16][17][18][19]. The balance between these two objectives of the cost function is achieved through a control penalty factor (ρ), which weights the significance of the second quadratic term in the criterion function.…”

Section: Introductionmentioning

confidence: 99%

“…However, a too low penalization of the control is the main cause that can destabilize the control system. A proper value of ρ, neither too small nor too big, could be a compromise solution [12,16,17].…”

Section: Introductionmentioning

confidence: 99%

“…For a control system having as its main objective the rejection of the disturbance effect, two situations can be considered, depending on the possibility of measuring the disturbance. For the case when the disturbance is directly measurable, a strategy for on-line tuning of the control penalty factor was described by the authors in [17]. For the case when the disturbance is not directly measurable, a tuning strategy can be designed by considering an indirect measurement of disturbance, more precisely, by measuring the disturbing effect produced by it (this being the subject of this paper).…”

Section: Introductionmentioning

confidence: 99%

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Minimum-Variance Control System with Variable Control Penalty Factor

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The present paper proposes (as the main contribution) an additional self-tuning mechanism for an adaptive minimum-variance control system, whose main goal is to extend its functionality for a large value range of unmeasurable perturbations which disturb the controlled process. Through the standard design procedure, a minimum variance controller uses by default an internal self-tuning mechanism based on the process parameter estimates. However, the main parameter which overwhelmingly influences the control performance is the control penalty factor ( ρ ) . This parameter weights the term that describes the control variance in a criterion function whose minimization is the starting point of the control law design. The classical minimum-variance control involves an off-line tuning of this parameter, its value being set as constant throughout the entire operating regime. Based on the measurement of the process output error, the contribution of the proposed strategy consists in a real-time tuning of the control penalty factor, to ensure the stability of the control system, even under conditions of high disturbances. The proposed tuning mechanism adjusts this parameter by implementing a bipositional switching strategy based on a sharp hysteresis loop. Therefore, instead of the standard solution that involves a constant value of the control penalty factor ρ (a priori computed and set), this paper proposes a dual value for this controller parameter. The main objective is to allow the controlled process to operate in a stable fashion even in more strongly disturbed regimes (regimes where the control system becomes unstable and is usually switched off for safety reasons). To validate the proposed strategy, an induction generator integrated into a wind energy conversion system was considered as controlled plant. Operating under the action of strong disturbances (wind gusts, electrical load variations), the extension of safe operating range (thus avoiding the system disengagement) is an important goal of such a control system.

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“…The control law design involves minimizing a cost function described by relation (4) [15][16][17][18]:…”

Section: Design Of the Minimum Variance Control Lawmentioning

confidence: 99%