Ein Prädiktionsansatz zum Entwurf linearer und nichtlinearer Regelungen/ A predictive approach to the design of linear and nonlinear controllers

1992 ◽  
Vol 40 (5) ◽  
Author(s):  
Boris Lohmann
2020 ◽  
Vol 9 (5) ◽  
pp. 1861-1872
Author(s):  
M. Madark ◽  
A. Ba-razzouk ◽  
M. El Malah

This paper provided a comparative study between linear and nonlinear controllers of a solar photovoltaic (PV) water pumping system using an induction motor and a centrifugal pump. For linear controller, classical Perturb and Observe was selected to ensure the operation of the PV system at the maximum power point (MPP) and is combined with Indirect Rotor Field Oriented Control (IRFOC) based on a conventional proportional integral speed regulator chosen to control and to optimize the rotor speed. In second and third controllers, Backstepping and first order sliding mode controls were proposed for controlling the whole system. To regulate and optimize rotor speed in the nonlinear controller, all considered control techniques were combined with IRFOC in order to establish easy control laws. In addition, MPP was tracked by acting on the DC-DC converter and using its mathematical model for developing control laws. Maximum delivered power was used as reference signal for optimizing actual rotor speed. The controlled system is operated without mechanical sensors. Estimators of rotor speed and load torque were proposed based on the mathematical model of induction motor and centrifugal pump and using only available output measurements.. Simulation results were investigated and the effectiveness of the nonlinear proposed strategies.


2004 ◽  
Vol 10 (7) ◽  
pp. 979-993 ◽  
Author(s):  
Ahmad M. Harb ◽  
Issam A. Smadi

In this paper, we introduce the control of the strange attractor, chaos. Because of the importance of controlling undesirable behavior in systems. researchers are investigating the use of linear and nonlinear controllers, either to remove such oscillations (in power systems) or to match two chaotic systems (in secure communications). The idea of using the fuzzy logic concept for controlling chaotic behavior is presented. There are two good reasons for using fulzy control: first, there is no mathematical model available for the process; secondly. it can satisfy nonlinear control that can be developed empirically. without complicated mathematics. The two systems are well-known models so the first reason is not a big problem. and we can take advantage of the second reason.


2018 ◽  
Vol 16 (1) ◽  
pp. 392-396 ◽  
Author(s):  
Tadeo Espinoza-Fraire ◽  
Alejandro Dzul ◽  
Facundo Cortés-Martínez ◽  
Wojciech Giernacki

10.5772/53616 ◽  
2013 ◽  
Vol 10 (1) ◽  
pp. 33 ◽  
Author(s):  
Tadeo Espinoza ◽  
Alejandro Dzul ◽  
Miguel Llama

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