Design of an Automatic Control Algorithm for Energy-Efficient ...

More documents

Recommendations

Info

Optimiser code 166 552 for( k =0; k (basePop [ j∗DV.numDV+k] conDivThresh∗(DV.ub[ if(check) k] DV.lb[k])); 558 sortedPop [ i ]. ranking++; 560 check = 1; } /∗ find individuals close to chosen control output∗/ 562 for( k =0; k (elitePop [k] conDivThresh∗(DV.ub[k] DV.lb[k])); if(check) 568 sortedPop [ i ]. ranking++; 570 } /∗ store individuals with lowest neighbours in the storage for next run ∗/ 572 elite_count = 1; k = 0; 574 while(elite_count < numElite) { 576 for( i=0;i
Optimiser code 167 596 ∗ Printout a population for debugging 598 ∗/ 600 ∗ ======================================================================== int_T i , j ; printf(" \n" ) ; 602 for ( i =0; i
Page 1:
ISSN 0280-5316 ISRN LUTFD2/TFRT--58
Page 5:
Diploma thesis subject Problem stat
Page 8 and 9:
Acknowledgements ii Acknowledgement
Page 10 and 11:
Acknowledgements iv 3.1.4 Windscree
Page 12 and 13:
Acknowledgements vi 8.5 System simu
Page 14 and 15:
Nomenclature viii Nomenclature Symb
Page 16 and 17:
Nomenclature x Other symbols Symbol
Page 18 and 19:
Nomenclature xii Subscript Descript
Page 21 and 22:
1 Introduction Energy consumption t
Page 23 and 24:
1 Introduction 3 adjustment of the
Page 25 and 26:
2 Control objectives 5 2.1 Windscre
Page 27 and 28:
2 Control objectives 7 2.2 Comfort
Page 29 and 30:
2 Control objectives 9 � Metaboli
Page 31 and 32:
2 Control objectives 11 ��
Page 33 and 34:
2 Control objectives 13 Figure 2.6:
Page 35 and 36:
2 Control objectives 15 2.4 Influen
Page 37 and 38:
3 System description 17 or heat com
Page 39 and 40:
3 System description 19 calculated
Page 41 and 42:
3 System description 21 ��
Page 43 and 44:
3 System description 23 � � �
Page 45 and 46:
3 System description 25 defrost tem
Page 47 and 48:
3 System description 27 Figure 3.4:
Page 49 and 50:
3 System description 29 width modul
Page 51 and 52:
3 System description 31 ��
Page 53 and 54:
3 System description 33 shown in Fi
Page 55 and 56:
3 System description 35 of performa
Page 57 and 58:
4 Control strategy The main goal of
Page 59 and 60:
4 Control strategy 39 limits are di
Page 61 and 62:
4 Control strategy 41 ��
Page 63 and 64:
4 Control strategy 43 cabin. This s
Page 65 and 66:
4 Control strategy 45 controlled. T
Page 67 and 68:
5 The disturbance estimator 47 in e
Page 69 and 70:
6 The optimiser: an evolutionary al
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
7 The HVAC-system controller 69 �
Page 91 and 92:
7 The HVAC-system controller 71 7.5
Page 93 and 94:
8 System and functionality integrat
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
Page 115 and 116:
9 The MUTE project 95 order to fit
Page 117 and 118:
10 Hardware and characteristics of
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
11 Matlab implementation The climat
Page 131 and 132:
11 Matlab implementation 111 Only r
Page 133 and 134:
11 Matlab implementation 113 left i
Page 135 and 136: 11 Matlab implementation 115 tion a
Page 137 and 138: 12 Controller evaluation 117 ��
Page 139 and 140: 12 Controller evaluation 119 be not
Page 141 and 142: 12 Controller evaluation 121 Number
Page 143 and 144: 12 Controller evaluation 123 Table
Page 145 and 146: 12 Controller evaluation 125 In the
Page 147 and 148: 12 Controller evaluation 127 ��
Page 149 and 150: 13 Conclusion 129 13.2 Possible imp
Page 151 and 152: Bibliography [1] Holger Großmann.
Page 153 and 154: Bibliography 133 [22] M. Wang, T.M.
Page 155 and 156: Appendices
Page 157 and 158: B In- and outputs The interface bet
Page 159 and 160: Signal Unit Range Type Comment Stat
Page 161 and 162: In- and outputs 141 B.3 Error codes
Page 163 and 164: and system parameters 2 concentrati
Page 165 and 166: Simulation parameters 145 C.2 Contr
Page 167 and 168: Simulation parameters 147 Panic han
Page 169 and 170: Simulation parameters 149 C.5 Test
Page 171 and 172: Additional simulation results 151 D
Page 173 and 174: Optimiser code 153 real_T ∗panic_
Page 175 and 176: Optimiser code 155 52 return 10; 54
Page 177 and 178: Optimiser code 157 138 /∗ return
Page 179 and 180: Optimiser code 159 230 ∗/ ∗ ===
Page 181 and 182: Optimiser code 161 ∗ IMEA_breedin
Page 183 and 184: Optimiser code 163 414 } 416 } } st
Page 185: Optimiser code 165 if (sortedPop [
Page 189: Optimiser code 169 690 ∗ Latest R
show all

Design of an Automatic Control Algorithm for Energy-Efficient ...

Create successful ePaper yourself

Delete template?

Save as template?