An Overview of Impact of Nonlinear Friction in Oscillating Control Loops: from Diagnosis to Compensation


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Abstract


Among the prominent reasons for oscillations in control loops such as poor controller tuning, inappropriate process design, oscillating load and disturbances with a high-frequency, the presence of static friction or stiction in the control valve is the most common reason. As a consequence of the friction, the control valves may present an oscillatory behavior, affecting the regulatory control performance and therefore it increases the variability of the control loop, causing loss of product quality and increasing energy consumption. Modeling of stiction using clear mathematical definition is hard due to its nonlinearity properties such as hysteresis, deadband or deadzone. This comparative study identifies the relative strengths and weaknesses of the different approaches of diagnosing of stiction in control loops and the compensation techniques to mitigate this effect. The aim is to determine the appropriate and precise model of stiction in order to design a proper controller to prevent control loops from oscillations. Numerous algorithms and methods which are either qualitative or quantitative in the literature show that despite these attempts to modeling, diagnosing and compensation of this phenomenon, lack of a reliable methodology to predict occurrence and properties of such oscillations and therefore lack of proper model is quite sensible. Furthermore exclusive of lack of precise model, even solving the problem were limited to some and different assumptions and applications and there is not one method which can cover all cases reliably. From this study too, it is seen that Data Driven model because of providing a simpler solution with fewer parameters is the most common method in contrast to physical based models with the presence of a number of unknown physical parameters. It is our view that hybrid approaches where different methods work in conjunction to solve parts of the problem are attractive and more effective methods. Lastly, numerous methods of stiction detection are available. Hence, it is suggested that the future research emphasis should be more on compensation of stiction especially for nonlinear processes.
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Keywords


Stiction; Diagnosis; Valve; Data-Driven

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