This paper focuses on the indirect adaptive tracking control of renewable energy
sources in a grid-connected hybrid power system. The renewable energy systems
have low efficiency and intermittent nature due to unpredictable meteorological
conditions. The domestic load and the conventional charging stations behave in an
uncertain manner. To operate the renewable energy sources efficiently for
harvesting maximum power, instantaneous nonlinear dynamics should be captured
online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT
(maximum power point tracking) control paradigm is proposed for variable speed
wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermitewavelet
incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic
(PV) system to extract maximum power and indirect adaptive tracking control
scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation
test-bed for a gridconnected hybrid power system is developed in Matlab/Simulink.
The robustness of the suggested indirect adaptive control paradigms are evaluated
through simulation results in a grid-connected hybrid power system test-bed by
comparison with conventional and intelligent control techniques. The simulation
results validate the effectiveness of the proposed control paradigms.

제 1편 : SIMULINK 기본편
1.1 SIMULINK의 시작 1
블록의 연결 5
블록 파라미터의 설정 7
시뮬레이션 파라미터 (Configuration Parameters)의 설정 8
시뮬레이션의 수행 9
블록 파라미터의 표시 9
복수 데이터의 표시 11
2.2 동적 시뮬레이션 13
이차 미분방정식 17
선형 상태변수 모델 23
DC 모터의 시뮬레이션 24
함수 블록의 사용 29
차분방정식(difference equation)의 모델링 34
Subsystem(부시스템)의 구성 37

제 2편 : 연구논문
Indirect adaptive soft computing based wavelet-embedded control
paradigms for WT/ PV/SOFC in a grid/charging station connected
hybrid power system

1. Introduction 41
2. Problem formulation 44
3. VSWT-PMSG MPPT subsystem adaptive control design 46
4. SOFC adaptive control problem 52
5. Mathematical modeling 54
6. Results and discussion 59
7. Conclusion 69
8. References 70