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ISBN : 978-89-7868-282-4
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Matlab/Simulink¸¦ Áß½ÉÀ¸·Î¡ºÆÛÁö½Å°æ¸Á Á¦¾î¡». ¿ï»ê´ëÇб³ °ø°ú´ëÇÐ ±â°è°øÇкΠÀ̺´·æ ±³¼ö°¡ ±× µ¿¾È ¼öÁýÇØ¿Ô´ø °­ÀÇÀڷḦ Åä´ë·Î ÆÛÁö ¹× ½Å°æ¸ÁÀ» °øºÎÇÏ´Â ÇлýµéÀ» À§ÇØ ÁýÇÊÇÑ ±³ÀçÀÌ´Ù. ¼³°èÀÇ ±âº»¹æ¹ý ¹× ±âÁ¸ÀÇ Á¦¾î½Ã½ºÅÛ¿¡ °áÇÕÇÏ´Â ¹æ¹ý µîÀ» ÀÚ¼¼È÷ ¼³¸íÇÏ°í Matlab/Simulink¸¦ ÀÌ¿ëÇÏ¿© Á¢±ÙÇÏ´Â ¹æ¹ýÀ» »ó¼¼È÷ ¼³¸íÇÏ¿© ½ÇÁúÀûÀÎ µµ¿òÀÌ µÇµµ·Ï ±¸¼ºÇÏ¿´´Ù. ÇлýµéÀÌ ÆÛÁö ¹× ½Å°æ¸Á ½Ã½ºÅÛÀ» ½±°Ô ¼³°èÇÏ°í Á¦¾îÇÒ ¼ö ÀÖµµ·Ï ¼³°è ´Ü°èº°·Î ¼³¸íÇÏ¿´À¸¸ç, ÆÛÁö ¹× ½Å°æ¸ÁÀÇ ÇÁ·Î±×·¡¹ÖÀÌ ¾î¶»°Ô ÀÌ·ç¾î Áö´ÂÁö¸¦ MatlabÀ¸·Î ÀÛ¼ºÇÑ ÇÁ·Î±×·¥À» ÀÌ¿ëÇÏ¿© ¿ä¼Òº°·Î È®ÀÎÇÒ ¼ö ÀÖµµ·Ï ÇÏ¿´´Ù.

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1Àå SimulinkÀÇ ±âÃÊ / 7
   1. Simulink ¼Ò°³ / 7
   2. SimulinkÀÇ »ç¿ë¹ý 8
   3. ¿¬¼Ó½Ã½ºÅÛ(Continuous system) / 14
   4. ¼­ºê½Ã½ºÅÛ(Subsystem)ÀÇ »ý¼º / 26
   5. Embedded MATLAB Function »ç¿ë / 30
   6. S-FunctionÀÇ »ç¿ë / 33


2Àå ÆÛÁö ½Ã½ºÅÛ / 43
   1. ÆÛÁö ÁýÇÕ(Fuzzy set) / 43
   2. ÆÛÁö ½Ã½ºÅÛ / 46
   3. ÆÛÁö ½Ã½ºÅÛÀÇ ±¸¼º¹æ¹ý / 48
   4. ÆÛÁö ½Ã½ºÅÛÀÇ µ¿ÀÛ / 53
   5. Sugeno ÆÛÁö ½Ã½ºÅÛ / 58


3Àå ÆÛÁö Á¦¾î / 63
   1. MatlabÀ» ÀÌ¿ëÇÑ ÆÛÁöÁ¦¾î / 63
   2. MATLAB ÆÛÁö Åø¹Ú½º¸¦ ÀÌ¿ëÇÑ ÆÛÁöÁ¦¾î / 75
   3. MATLAB ÆÛÁö Åø¹Ú½º¸¦ ÀÌ¿ëÇÑ Sugeno ¹æ½Ä ÆÛÁöÁ¦¾î / 85
   4. Simulink¸¦ ÀÌ¿ëÇÑ ÆÛÁöÁ¦¾î / 89


4Àå ÆÛÁö Á¦¾î½Ã½ºÅÛÀÇ ÀÀ¿ë»ç·Ê / 113
   1. ÆÛÁö Á¦¾î±â¸¦ ÀÌ¿ëÇÑ DC ¸ðÅÍÀÇ Á¦¾î / 113
   2. ¹Ý´Éµ¿(Semi-active) ÀÚµ¿Â÷ Çö°¡½Ã½ºÅÛÀÇ ÆÛÁöÁ¦¾î / 127
   3. Àå¾Ö¹° ¿ìȸ ±â´ÉÀ» °®´Â ´Ù°üÀý Áö´É ·Îº¿ ½Ã½ºÅÛ / 144


5Àå Àΰø½Å°æ¸Á(Artificial Neural Network) / 157
   1. Àΰø½Å°æ¸ÁÀÇ °³³ä / 157
   2. ´ÙÃþ±¸Á¶ÀÇ ½Å°æ¸Á(Multi-Layer feedforward Neural Networks) / 159
   3. ½Å°æ¸ÁÀÇ ÇнÀ(training) / 162
   4. ½Å°æ¸Á ÇнÀÀ» À§ÇÑ ³ëÇÏ¿ì / 168


6Àå ½Å°æ¸ÁÀÇ ÇÁ·Î±×·¡¹Ö / 171
   1. MatlabÀ» ÀÌ¿ëÇÑ ½Å°æ¸ÁÀÇ ÇнÀ / 171
   2. MATLABÀÇ ½Å°æ¸Á ÇÔ¼ö¸¦ ÀÌ¿ëÇÑ ½Å°æ¸ÁÀÇ ÇнÀ / 183
   3. MATLAB TOOLBOX¸¦ ÀÌ¿ëÇÑ ½Å°æ¸ÁÀÇ ÇнÀ / 187


7Àå ½Å°æ¸Á Á¦¾î±â / 199
   1. ½Å°æ¸Á ÇнÀÀÇ Á¾·ù / 199
   2. ½Å°æ¸Á ¿ªÁ¦¾î±â 200
   3. KawatoÀÇ ½Å°æ¸Áº´·ÄÁ¦¾î±â / 201
   4. ½Å°æ¸ÁÀ» ÀÌ¿ëÇÑ ±âÁظ𵨠ÀûÀÀÁ¦¾î±â / 202
   5. ½Å°æ¸Á ¸ðµ¨¿¹ÃøÁ¦¾î(NN Predictive Control) / 211
   6. ANFIS(Adaptive Network Based Fuzzy Inference Systems) / 223


8Àå ȸ±Í ½Å°æ¸Á(Recurrent Neural Network) / 243
   1. Elman ½Å°æ¸Á / 243
   2. Hopfield ½Å°æ¸Á / 248


9Àå Àڱⱸ¼º(Self-Organizing) ½Å°æ¸Á / 255
   1. °æÀïÇнÀ(Competitive Learning) ½Å°æ¸Á / 255
   2. SOFM(Self-Organizing Feature Maps) ½Å°æ¸Á / 262


10Àå ½Å°æ¸Á Á¦¾îÀÇ ÀÀ¿ë»ç·Ê / 269
   1. ½Å°æ¸Á-PID Á¦¾î±â¸¦ ÀÌ¿ëÇÑ ¾ÐÀü±¸µ¿±â Á¦¾î½Ã½ºÅÛ / 269
   2. ½Å°æ¸ÁÀÚ°¡Á¶Á¤(SELF-TUNING) PID Á¦¾î±â¸¦ ÀÌ¿ëÇÑ ¼öÁ¶ ·¹º§ Á¦¾î / 279


ã¾Æº¸±â / 291