Approximated Simplest Fuzzy Logic Controlled Shunt Active Power Filter for Current Harmonic Mitigation

2011 ◽  
Vol 1 (4) ◽  
pp. 18-36 ◽  
Author(s):  
Rambir Singh ◽  
Asheesh K. Singh ◽  
Rakesh K. Arya

This paper examines the size reduction of the fuzzy rule base without compromising the control characteristics of a fuzzy logic controller (FLC). A 49-rule FLC is approximated by a 4-rule simplest FLC using compensating factors. This approximated 4-rule FLC is implemented to control the shunt active power filter (APF), which is used for harmonic mitigation in source current. The proposed control methodology is less complex and computationally efficient due to significant reduction in the size of rule base. As a result, computational time and memory requirement are also reduced significantly. The control performance and harmonic compensation capability of proposed approximated 4-rule FLC based shunt APF is compared with the conventional PI controller and 49-rule FLC under randomly varying nonlinear loads. The simulation results presented under transient and steady state conditions show that dynamic performance of approximated simplest FLC is better than conventional PI controller and comparable with 49-rule FLC, while maintaining harmonic compensation within limits. Due to its effectiveness and reduced complexity, the proposed approximation methodology emerges out to be a suitable alternative for large rule FLC.

Author(s):  
Rambir Singh ◽  
Asheesh K. Singh ◽  
Rakesh K. Arya

This paper examines the size reduction of the fuzzy rule base without compromising the control characteristics of a fuzzy logic controller (FLC). A 49-rule FLC is approximated by a 4-rule simplest FLC using compensating factors. This approximated 4-rule FLC is implemented to control the shunt active power filter (APF), which is used for harmonic mitigation in source current. The proposed control methodology is less complex and computationally efficient due to significant reduction in the size of rule base. As a result, computational time and memory requirement are also reduced significantly. The control performance and harmonic compensation capability of proposed approximated 4-rule FLC based shunt APF is compared with the conventional PI controller and 49-rule FLC under randomly varying nonlinear loads. The simulation results presented under transient and steady state conditions show that dynamic performance of approximated simplest FLC is better than conventional PI controller and comparable with 49-rule FLC, while maintaining harmonic compensation within limits. Due to its effectiveness and reduced complexity, the proposed approximation methodology emerges out to be a suitable alternative for large rule FLC.


2012 ◽  
Vol 2 (3) ◽  
pp. 69-89 ◽  
Author(s):  
Rambir Singh ◽  
Asheesh K. Singh

This paper presents the design and analysis of an improved approximated simplest fuzzy logic controller (IASFLC). A cascade combination of simplest 4-rule fuzzy logic controller (FLC) and an nth degree polynomial is proposed as an IASFLC to approximate the control characteristics of a 49-rule FLC. The scheme is based on minimizing the sum of square errors between the control outputs of a 49-rule FLC and a simplest 4-rule FLC in the entire range of universe of discourse (UOD). The coefficients of compensating polynomial are evaluated by solving instantaneous square error equations at various test points in the entire UOD. This IASFLC maps the output of a 49-rule FLC with absolute deviation of less than 5%. The proposed IASFLC is used to control the dc link voltage of a three phase shunt active power filter (APF). A detailed analysis is performed during transient and steady state conditions to check power quality (PQ) and dynamic performance indices. The performance of proposed IASFLC is compared with a 49-rule FLC and approximated simplest fuzzy logic controller (ASFLC) based on minimization of the deviation at central values of membership functions (MFs). It is found comparatively better for harmonic and reactive compensation with a comparable dynamic response. The memory requirement and computational time of proposed IASFLC are less than the ASFLC.


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