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Figure 8 Simulated current response of LLC-RC under line disturbance (40V-38V-40V) at t=0.55sec. Figure 7 Simulated voltage response of LLC-RC under line disturbance (40V-38V-40V) at t=0.55sec.

Figure 8 Simulated current response of LLC-RC under line disturbance (40V-38V-40V) at t=0.55sec. Figure 7 Simulated voltage response of LLC-RC under line disturbance (40V-38V-40V) at t=0.55sec.

Related Figures (23)

Fig 1. Circuit diagram of modified LLC Resonant - Boost Converter
Fig 1. Circuit diagram of modified LLC Resonant - Boost Converter
Figure 2 Block diagram of LLC Resonant Converter Fed Resistive Load using PI Controlle The Proportional integral (PI) controller is amongst the conventional controllers. It is mostly used to control the speed. The major feature of the PI controller is the capability to keep constant zero steady-state error. The combination of PI is essential to raise the speed of the system response and to reduce the steady-state error. The circuit errors are reduced by trial and error method. The controlled signals are given to RC and Linear transformer [15]. The Pl controllers are a special case; they are usually used for controlling various systems. It has some errors such as proportional and integral errors. Then the output is increased by terms of proportional constant Kp. The integral error also affects the output values [16-17].The output is increased in terms of integral constant Kj. The gain K,and K; are correcting ports to modify the preferred output response. The PI controller has the advantages of increasing system stability. Figure 2 Shows the Block diagram of LLC Resonant Converter Fed Resistive Load using PI Controller.
Figure 2 Block diagram of LLC Resonant Converter Fed Resistive Load using PI Controlle The Proportional integral (PI) controller is amongst the conventional controllers. It is mostly used to control the speed. The major feature of the PI controller is the capability to keep constant zero steady-state error. The combination of PI is essential to raise the speed of the system response and to reduce the steady-state error. The circuit errors are reduced by trial and error method. The controlled signals are given to RC and Linear transformer [15]. The Pl controllers are a special case; they are usually used for controlling various systems. It has some errors such as proportional and integral errors. Then the output is increased by terms of proportional constant Kp. The integral error also affects the output values [16-17].The output is increased in terms of integral constant Kj. The gain K,and K; are correcting ports to modify the preferred output response. The PI controller has the advantages of increasing system stability. Figure 2 Shows the Block diagram of LLC Resonant Converter Fed Resistive Load using PI Controller.
Figure 3 Block diagram of LLC Resonant Converter Fed Resistive Load using Fuzzy Controllet es, ee FLC works under the principle of FUZZY logics. Fuzzy logic provides conventional and us« friendly frontend to develop the control programs. Fuzzy controllers have the tendency 1 oscillate around the final operating point [18].It is the processes of converting the crisp dat into a linguistic member function. For the given input and output the mapping is formulate: There are seven linguistic member functions. They are NB, N, NS, ZE, PS, P, PB. It is dor by using Takagi-Suge no method [19-20]. Fuzzy logic is a very powerful tool and successfi implementation in every field. Fuzzy controller has several advantages over PI controller. Th fuzzy controller is more beneficial because of its simple design, robust, cheap, and multip! inputs and multiple outputs. Figure 3 Shows the Block diagram of LLC Resonant Convert Fed Resistive Load using Fuzzy Controller.
Figure 3 Block diagram of LLC Resonant Converter Fed Resistive Load using Fuzzy Controllet es, ee FLC works under the principle of FUZZY logics. Fuzzy logic provides conventional and us« friendly frontend to develop the control programs. Fuzzy controllers have the tendency 1 oscillate around the final operating point [18].It is the processes of converting the crisp dat into a linguistic member function. For the given input and output the mapping is formulate: There are seven linguistic member functions. They are NB, N, NS, ZE, PS, P, PB. It is dor by using Takagi-Suge no method [19-20]. Fuzzy logic is a very powerful tool and successfi implementation in every field. Fuzzy controller has several advantages over PI controller. Th fuzzy controller is more beneficial because of its simple design, robust, cheap, and multip! inputs and multiple outputs. Figure 3 Shows the Block diagram of LLC Resonant Convert Fed Resistive Load using Fuzzy Controller.
Figure 4 Block diagram of LLC Resonant Converter Fed Resistive Load using Neural Controller Figure 4 Block diagram of LLC Resonant Converter Fed Resistive Load using Neural Controller output data are important to obtain the desired output values. The data set is adequate and enough to confirm the constant operation. So there is no requirement of erudite after operation. In the Neural Controller the feedback system and pre-filters are multilayered. The Neural controller has different models such as Single input and multiple input models. The rear transmission procedure is used to run the constructed network. This procedure is commonly controlled transmission system for multilayered network. Figure 4 Shows the Block diagram of LLC Resonant Converter Fed Resistive Load using Neural Controller.
Figure 4 Block diagram of LLC Resonant Converter Fed Resistive Load using Neural Controller Figure 4 Block diagram of LLC Resonant Converter Fed Resistive Load using Neural Controller output data are important to obtain the desired output values. The data set is adequate and enough to confirm the constant operation. So there is no requirement of erudite after operation. In the Neural Controller the feedback system and pre-filters are multilayered. The Neural controller has different models such as Single input and multiple input models. The rear transmission procedure is used to run the constructed network. This procedure is commonly controlled transmission system for multilayered network. Figure 4 Shows the Block diagram of LLC Resonant Converter Fed Resistive Load using Neural Controller.
Figure 5 Simulated voltage response of LLC-RC under nominal load 100Q and input voltage 40V.
Figure 5 Simulated voltage response of LLC-RC under nominal load 100Q and input voltage 40V.
Figure 6 Simulated current response of LLC-RC under nominal load 100Q and input voltage 40V.
Figure 6 Simulated current response of LLC-RC under nominal load 100Q and input voltage 40V.
Figure 9 Simulated voltage response of LLC-RC under load disturbance (100Q-90Q-100Q) at t=0.55sec. Under Load Disturbance
Figure 9 Simulated voltage response of LLC-RC under load disturbance (100Q-90Q-100Q) at t=0.55sec. Under Load Disturbance
Under Line Disturbance
Under Line Disturbance
Under Nil Disturbance Figure 11 Simulated voltage response of LLC-RC under nominal load 100Q and input voltage 40V. 4.2. Fuzzy Controller
Under Nil Disturbance Figure 11 Simulated voltage response of LLC-RC under nominal load 100Q and input voltage 40V. 4.2. Fuzzy Controller
Figure 12 Simulated current response of LLC-RC under nominal load 100Q and input voltage 40V.
Figure 12 Simulated current response of LLC-RC under nominal load 100Q and input voltage 40V.
Under Line Disturbance
Under Line Disturbance
Under Nil Disturbance figure 17 Simulated voltage response of LLC-RC under nominal load 100Q and input voltage 40V.
Under Nil Disturbance figure 17 Simulated voltage response of LLC-RC under nominal load 100Q and input voltage 40V.
Figure 18 Simulated current response of LLC-RC under nominal load 100Q and input voltage 40V.
Figure 18 Simulated current response of LLC-RC under nominal load 100Q and input voltage 40V.
Figure 22 Simulated current response of LLC-RC under load disturbance (100Q-90Q-100Q) at t=0.55sec.
Figure 22 Simulated current response of LLC-RC under load disturbance (100Q-90Q-100Q) at t=0.55sec.
Table 1 Comparison of various parameters of different controllers under nominal load 100Q.
Table 1 Comparison of various parameters of different controllers under nominal load 100Q.
Figure 23 Comparison graph of different parameters of various controllers under nominal load 100Q.
Figure 23 Comparison graph of different parameters of various controllers under nominal load 100Q.
Related topics:
Fuzzy ControllerPI ControllerNeural ControllerLLC resonant converter
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