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Process Control
Published in Dale R. Patrick, Stephen W. Fardo, Industrial Process Control Systems, 2021
Dale R. Patrick, Stephen W. Fardo
Control is a system concept that takes on many different meanings, but the basic idea of control is the primary influence that it has on the final outcome of a process or operation. As such, control must be achieved before the final outcome is decided. Control effectiveness is primarily influenced by response time and accuracy of measurement, comparison, computation, and correction. Control of industrial processes can be achieved by open-loop or closed-loop systems. Open-loop control involves a great deal of physical effort by the operator. Closed-loop control employs a feedback path that samples the output to control the process automatically.
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Published in Philip A. Laplante, Comprehensive Dictionary of Electrical Engineering, 2018
stability (1) the condition of a dynamic or closed-loop control system in which the output or controlled variable always corresponds, at least approximately, to the input or command within a limited range. In most devices, this is a measure of the inherent ability of the circuit to avoid internally generated oscillations. In oscillators, stability denotes the ability of the circuit to maintain a stable internally generated amplitude and frequency. The circuit components, bias, loading, drive and environmental conditions, and possible variations therein, must be accounted
An Overview of Applied Control Engineering
Published in Cheng Siong Chin, Computer-Aided Control Systems Design, 2017
Closed-loop control or feedback is the action of measuring the difference between the actual output and desired value, and using that difference to drive the actual output toward desired value. The term feedback comes from the direction in which the measured output travels in the block diagram. The signal begins at the output of the controlled system and ends at the input of the controller. Closed-loop control systems are the type most commonly used in industry because they control with greater accuracy than open-loop systems in Figure 1.3.
Study on Passive Control of the Self-excited Thermoacoustic Oscillations Occurring in Combustion Systems
Published in Combustion Science and Technology, 2023
Yuanhang Zhang, Chang’An Wang, Xuan Liu, Yongbo Du, Defu Che
The control of SETAOs has attracted much attention in recent years, which can be divided into active and passive control strategies (Dowling and Morgans 2005). Active control is a strategy for controlling the parameters of combustion systems through an actuator to destroy the coupling between pressure fluctuations and heat release fluctuations (Dowling and Morgans 2005). There are two different active control strategies: closed-loop control (feedback control) and open-loop control. In feedback control, a sensor is used to feedback the signal to the actuator to control the system parameters. On the contrary, there is no signal feedback system in open-loop control. Various active control methods were investigated by many researchers (Guan et al. 2019; Kashinath, Li, Juniper 2018; Paschereit, Gutmark, Weisenstein 2007; Wu et al. 2018b; Yazar, Caliskan, Vepa 2018; Zhao and Li 2012). It was shown that closed-loop control and open-loop control were both effective methods to mitigate thermoacoustic oscillations. However, active control would increase the complexity of the combustion system and consume extra energy. In addition, oscillations may increase if not properly controlled (Wu et al. 2018b). Especially for closed-loop control, the reliability of sensors and actuators cannot be guaranteed in practical industrial applications (Guan et al. 2019; Mongia et al. 2003).
Machine learning based predictive modeling and control of surface roughness generation while machining micro boron carbide and carbon nanotube particle reinforced Al-Mg matrix composites
Published in Particulate Science and Technology, 2022
Ravi Sekhar, T. P. Singh, Pritesh Shah
In the past, researchers have extensively investigated various analytical and statistical approaches to model various aspects of micro composite machining (Pramanik, Zhang, and Arsecularatne 2006, 2008; Sikder and Kishawy 2012). However, most of these models cannot be implemented in a closed loop industrial control system for automating the composite machining process. Industrial process automation typically requires parametric models that can be implemented in a suitable controller architecture for closed loop control. Closed loop control is a real time sensor feedback driven system wherein the controller automatically manipulates input parameters to maintain the process output at the desired set point. This real time process control is critically dependent upon the accuracy of the parametric model defining the relationship between the input and the output parameters. Accurate parametric models can be derived effectively by the implementation of system identification methodology. System identification employs actual input/output data sets to ‘identify’ models that describe the real system behavior based on existing parametric structures. System identification based parametric modeling has been successfully applied across various domains such as 3 D printing, structural damage prediction, robotics, fuel cells, HIV drug resistance, bio-diesel engines, bolted joint systems and many more (Silva, Machado, and Barbosa 2006; Giurgiutiu 2010; Shahiri et al. 2015; Pinto and Carvalho 2015; Pandit, Sekhar, and Shah 2019; Shah, Sekhar, and Singh 2021; Shah and Sekhar 2021).
A review of electro-hydraulic servovalve research and development
Published in International Journal of Fluid Power, 2018
Paolo Tamburrano, Andrew R. Plummer, Elia Distaso, Riccardo Amirante
In this regard, in Persson et al. (2017) and Stefanski et al. (2017) a generalised Prandtl–Ishlinskii model, fitted to experimental training data from the prototype valve, was used to model hysteresis empirically. This form of model is analytically invertible and is used to compensate for hysteresis in the prototype valve both open loop, and in several configurations of closed loop real-time control system. The closed-loop control configurations use PID (Proportional-Integral Derivative) control with either the inverse hysteresis model in the forward path or in a command feedforward path. Performance is compared to both open and closed-loop control without hysteresis compensation via step and frequency response results. Results show a significant improvement in accuracy and dynamic performance using hysteresis compensation.