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1 | (6) |
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7 | (36) |
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7 | (2) |
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9 | (5) |
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9 | (2) |
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11 | (3) |
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2.3 The classic parametric identification methods |
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14 | (9) |
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14 | (1) |
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2.3.2 Algorithmic methods |
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15 | (4) |
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2.3.3 Validation and estimation of the model identified |
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19 | (4) |
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23 | (17) |
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23 | (1) |
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2.4.2 Techniques for obtaining multi-models |
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23 | (17) |
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40 | (3) |
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43 | (60) |
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43 | (39) |
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43 | (1) |
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3.1.2 The Smith predictor |
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44 | (5) |
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3.1.3 Predictive functional control |
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49 | (6) |
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3.1.4 Generalized predictive control |
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55 | (5) |
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60 | (3) |
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3.1.6 Implementation of the advance algorithms on a programmable logic controller: results |
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63 | (19) |
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82 | (16) |
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82 | (1) |
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83 | (3) |
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3.2.3 State feedback control |
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86 | (4) |
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3.2.4 Reconstructed state feedback control |
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90 | (3) |
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3.2.5 Static output feedback control |
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93 | (4) |
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97 | (1) |
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98 | (5) |
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Chapter 4 Application to Cryogenic Systems |
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103 | (62) |
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103 | (9) |
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4.1.1 Cryogenics and its applications at CERN |
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103 | (6) |
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4.1.2 Some basics about cryogenics |
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109 | (3) |
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4.2 Modeling and control of a cryogenic exchanger for the NA48 calorimeter at CERN |
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112 | (16) |
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4.2.1 Description of the cryogenic installations in the NA48 calorimeter |
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115 | (3) |
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118 | (2) |
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4.2.3 The TDC (Time Delay Control) corrector: application to a liquid-krypton cryogenic exchanger |
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120 | (8) |
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4.3 Modeling and control of the cryogenics of the ATLAS experiment at CERN |
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128 | (30) |
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4.3.1 Context and objectives of the study |
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128 | (2) |
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4.3.2 Process of identification of cryogenic systems |
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130 | (6) |
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4.3.3 Experimental protocol of parametric identification |
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136 | (6) |
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4.3.4 Mono-variable system |
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142 | (7) |
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4.3.5 Compensation for the delay with a Smith controller based on the PI corrector UNICOS |
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149 | (2) |
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4.3.6 Multi-variable system |
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151 | (7) |
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158 | (2) |
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159 | (1) |
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160 | (1) |
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160 | (4) |
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160 | (4) |
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164 | (1) |
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Chapter 5 Applications to a Thermal System and to Gas Systems |
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165 | (38) |
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5.1 Advanced control of the steam temperature on exiting a superheater at a coal-burning power plant |
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165 | (9) |
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165 | (1) |
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5.1.2 The internal model corrector (IMC) |
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166 | (3) |
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5.1.3 Multi-order regulator: 4th-order IMC |
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169 | (2) |
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171 | (3) |
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5.2 Application to gas systems |
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174 | (28) |
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174 | (6) |
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5.2.2 The major regulations |
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180 | (3) |
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5.2.3 The control system and acquisition of measurements |
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183 | (1) |
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5.2.4 Modeling, identification and experimental results |
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184 | (18) |
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202 | (1) |
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202 | (1) |
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Chapter 6 Application to Vehicles |
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203 | (120) |
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203 | (1) |
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6.2 Hydraulic excavator-loader |
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204 | (2) |
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6.2.1 Conventional manual piloting |
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205 | (1) |
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6.3 Principle of movement of a part of the arm |
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206 | (69) |
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6.3.1 Role of the drivers |
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206 | (1) |
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207 | (4) |
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6.3.3 Functional specification of the interface |
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211 | (27) |
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6.3.4 Limit of articular position and velocities |
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238 | (10) |
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248 | (11) |
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6.3.6 Limits of the articular velocities |
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259 | (8) |
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267 | (4) |
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6.3.8 Onboard computer architecture |
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271 | (4) |
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275 | (1) |
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275 | (44) |
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6.4.1 Models of automobiles |
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275 | (11) |
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6.4.2 Validation of vehicle models |
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286 | (12) |
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6.4.3 Robust control of the vehicle's dynamics |
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298 | (20) |
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318 | (1) |
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319 | (4) |
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Chapter 7 Real-time Implementation |
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323 | (40) |
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7.1 Implementation of algorithms on real-time targets around distributed architectures |
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323 | (24) |
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323 | (1) |
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7.1.2 Object-oriented programming in the case of a framework |
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324 | (9) |
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333 | (14) |
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7.2 A distributed architecture for control (rapidity/reliability): excavator-loader testing array |
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347 | (14) |
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7.2.1 Objectives of the testing array |
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347 | (1) |
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7.2.2 Presentation of the onboard computer platform |
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348 | (2) |
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7.2.3 Examination of the rapidity of the onboard computer structure |
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350 | (8) |
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358 | (3) |
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361 | (1) |
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362 | (1) |
General Conclusion |
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363 | (4) |
List of Authors |
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367 | (2) |
Index |
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369 | |