Modeling, plant uncertainties, and fuzzy logic sliding control of gaseous systems

Kiriakidis, Kiriakos; Tzes, Anthony; Grivas, Apostolos; Peng, Pei-Yuan

doi:10.1109/87.736749

Cited by 4 publications

(1 citation statement)

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“…The other problem with the SMC design is that the bounds of uncertainties and disturbances, which are most likely not available for many practical applications, must be known in determining the SMC switching gain. Progresses such as fuzzy adaptive tuning of the switching gain by Kiriakidis et al 7 and a fuzzy inference mechanism to estimate the uncertainty bound by Lin and Chiu 8 have been made to overcome this difficulty. These methods, however, require extensive process experience that may not be readily available in certain cases.…”

Section: Introductionmentioning

confidence: 99%

PID-Based Sliding Mode Controller for Nonlinear Processes

Wang

Gao

2001

Ind. Eng. Chem. Res.

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Sliding mode control (SMC) has excellent robustness to model uncertainties and disturbances. This would make SMC an ideal scheme for process control applications where model uncertainties and disturbances are common. The existing SMC, however, has the major drawback of control chattering; i.e., the controller output is a discontinuous high-frequency switching signal. This makes SMC not suitable for most chemical processes where the manipulated variables are continuous and where high-frequency changes are not permitted. To eliminate chattering, a new proportional-integral-derivative (PID)-based sliding mode control (PIDSMC) suitable for the chemical process is proposed here. The proposed control system consists of three components: a compensation of process nonlinearity, a linear feedback of state tracking errors, and a PID control of the sliding surface function. The chattering is eliminated via the replacement of the discontinuous switching in the SMC by a continuous input determined by a PID scheme. An adaptive strategy is proposed to tune the PID parameters online to control the process states onto a sliding surface that characterizes the closed-loop performance. The proposed algorithm has been shown to be effective in controlling an inverted pendulum system and a typical pH neutralization process.

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Section: Introductionmentioning

confidence: 99%