“…In the sequel, the variable control law with the Lyapunov control function will be defined as W(z 1 ) � (1/2)z 2 1 . e derivative of W with respect to time is obtained as…”
Section: Stability Analysis Of the Controlled Systemmentioning
confidence: 99%
“…In the few past decades, some researchers have invented the design and the implementation of the liquid level of a coupled-tank system controller such as the Proportional-Integral-Derivative (PID) type controllers [2], the backstepping controller [3,4], the nonlinear constrained predictive algorithms based on the feedback linearization control [5], the second-order sliding mode control [6], Constrained Pole Assignment Control (CPAC) [7,8], and neurofuzzy sliding mode controller (NFSMC) [9]. erefore, industrial process control engineering has immensely benefited from the technology development brought by digital computers and their sophisticated software.…”
This paper presents an implementation of two radically different control schemes for a state-coupled two-tank liquid-level system. This is due to the purpose of transferring theoretical studies to industrial systems. The proposed schemes to be introduced and compared are the nonsingular terminal sliding mode control (NTSMC) and the backstepping control (BC). The performances of the developed methods are experimentally tested on a particular class of second-order nonlinear systems. The main purpose of the considered control schemes is to achieve a tracking trajectory for a coupled-tank system. It is proved that the designed robust controllers guarantee the stability of the corresponding closed loop systems. The obtained results are verified with the same setup test to ensure a suitable basis for their comparison. During the experiments, we resorted to adding an integrator to the backstepping control so that we improve the results, leading to the appearance of the integrator backstepping control (IBC). To focus on the adequacy and applicability of the suggested control layout, theoretical comparisons as well as experimental results are afforded and debated.
“…In the sequel, the variable control law with the Lyapunov control function will be defined as W(z 1 ) � (1/2)z 2 1 . e derivative of W with respect to time is obtained as…”
Section: Stability Analysis Of the Controlled Systemmentioning
confidence: 99%
“…In the few past decades, some researchers have invented the design and the implementation of the liquid level of a coupled-tank system controller such as the Proportional-Integral-Derivative (PID) type controllers [2], the backstepping controller [3,4], the nonlinear constrained predictive algorithms based on the feedback linearization control [5], the second-order sliding mode control [6], Constrained Pole Assignment Control (CPAC) [7,8], and neurofuzzy sliding mode controller (NFSMC) [9]. erefore, industrial process control engineering has immensely benefited from the technology development brought by digital computers and their sophisticated software.…”
This paper presents an implementation of two radically different control schemes for a state-coupled two-tank liquid-level system. This is due to the purpose of transferring theoretical studies to industrial systems. The proposed schemes to be introduced and compared are the nonsingular terminal sliding mode control (NTSMC) and the backstepping control (BC). The performances of the developed methods are experimentally tested on a particular class of second-order nonlinear systems. The main purpose of the considered control schemes is to achieve a tracking trajectory for a coupled-tank system. It is proved that the designed robust controllers guarantee the stability of the corresponding closed loop systems. The obtained results are verified with the same setup test to ensure a suitable basis for their comparison. During the experiments, we resorted to adding an integrator to the backstepping control so that we improve the results, leading to the appearance of the integrator backstepping control (IBC). To focus on the adequacy and applicability of the suggested control layout, theoretical comparisons as well as experimental results are afforded and debated.
“…Many control systems have been developed and applied in irrigation networks to improve their performance (Litrico and Fromion, 2005;Stringam and Esplin, 2006;Ooi and Weyer, 2008;Isa et al, 2011;Li -fang, 2012;Figueiredo et al, 2013); some of them have succeeded and some have failed.…”
“…The most important element of the control system is a controller. Personal computers (PCs) connected to data acquisition (DAQ) cards [8]- [11], compact proportional-integral-derivative (PID) control devices [12], programmable logic controllers (PLCs) [13], [14], microcontrollers (μCs) [6], [15], [16] and digital signal processors (DSPs) [17] are the most commonly used controllers in practically all industrial control applications. These controllers interconnect all parts of the physical and non-physical of a system.…”
In engineering education, the combination with theoretical education and practical education is an essential problem. The taught knowledge can be quickly forgotten without an experimental application. In addition, the theoretical knowledge's cannot be easily associated applications by students when they start working in industry. To eliminate these problems, a number of education tools have been developed in engineering education. This article presents a modelling, simulation and practice study of a newly designed liquid level training set developed for the control engineering students to simulate, examine and analyze theoretically and experimentally the controllers widely used in the control of many industrial processes. The newly designed training set combines two control structures, which are a computer-based control and a digital signal processing-based control. The set displays the results related to experiments in real time as well as. These features have made it a suitable laboratory component on which the students can both simulate and test the performance of liquid level control systems by using theoretical different control structures.
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