Fuzzy gain scheduling design based on multiobjective particle swarm optimization

Costa, Edson Bruno Marques; Serra, Ginalber Luiz de Oliveira

doi:10.1109/la-cci.2015.7435970

Cited by 3 publications

(1 citation statement)

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“…The gains of the I-P-D controller parameters are updated according to the error and rate of change of error at each sample time constant by the Mamdani fuzzy algorithm [23,24]. In this control scheme, it is assumed that the controller gains are in prescribed ranges.…”

Section: Fgs I-p-d Control Structurementioning

confidence: 99%

Fuzzy Gain Scheduling of an I-P-D Controller for Oscillation Compensation in a Sticky Pneumatic Control Valve

Rohilla¹,

Kumar²,

Hakkak³

2016

IJMERR

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In the control loop, the pneumatic control valve is a highly nonlinear component with nonlinearities such as stiction, which induces the limit cycle and oscillations in the steady-state response. This paper successfully shows the elimination of oscillations from the process variable (PV) and controller output (OP) due to the sticky pneumatic control valve using a proposed control methodology, namely, fuzzy gain scheduling of an integral minus proportional minus derivative (FGS I-P-D) controller. The uniqueness of the proposed control method is that it is a standalone solution and it does not require any additional compensating component in the closed loop, as reported in the literature. In the I-P-D controller, integral action is performed on the error signal, whereas proportional and derivative actions are realized using the PV. The gains of the I-P-D controller were computed at runtime using a Mamdani-type fuzzy inference mechanism. The performance of the FGS I-P-D controller was compared with that of the conventional I-P-D controller for setpoint tracking capability and external disturbance rejection at different operating points on a laboratory scale pressure control unit. The experimental results clearly show that the FGS I-P-D controller outperformed the classical I-P-D controller in every aspect of investigation performed and suppressed efficiently any stiction-induced oscillations in PV and OP. 

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Section: Fgs I-p-d Control Structurementioning

confidence: 99%