Disturbance Observer-Based Adaptive Neural Network Control of Marine Vessel Systems with Time-Varying Output Constraints

<div>Trajectory of <span class="nowrap"><svg height="10.8962pt" id="M222" style="vertical-align:-3.29114pt" version="1.1" viewbox="-0.0498162 -7.60506 18.5489 10.8962" width="18.5489pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M642 327C642 461 565 582 389 582C298 582 219 548 176 519L185 491C235 515 291 526 348 526C477 526 572 452 572 268C572 145 509 51 431 51C396 51 366 78 366 145C366 189 391 295 402 337L396 341L320 332C315 289 306 229 296 187C276 99 230 55 185 55C149 55 111 89 111 170C111 275 160 373 238 431L222 457C99 394 23 290 23 157C23 40 81 -12 142 -12C185 -12 254 33 293 86C301 31 340 -12 394 -12C437 -12 477 8 524 50C589 108 642 203 642 327Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.32,3.132)"><path d="M538 684C542 703 539 710 529 710C512 710 455 682 363 674L361 644H396C444 644 448 642 438 594L405 438C373 450 347 451 336 451C288 451 200 416 147 374C69 312 24 207 24 113C24 29 60 -12 94 -12C126 -12 156 4 196 30C231 53 296 100 346 166H348L328 81C311 10 325 -12 348 -12C380 -12 450 24 512 98L495 125C466 97 431 70 417 70C408 70 408 80 411 98L538 684ZM390 373L361 240C336 196 210 56 145 56C132 56 113 73 113 131C113 216 156 338 220 379C243 394 266 402 303 402C331 402 375 388 390 373Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,13.453,3.132)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"></path></g></svg>,</span> <span class="nowrap"><svg height="9.14241pt" id="M223" style="vertical-align:-3.1815pt" version="1.1" viewbox="-0.0498162 -5.96091 16.7234 9.14241" width="16.7234pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M536 404C536 423 520 448 491 448C445 448 398 404 308 283L286 338C255 416 242 448 217 448C182 448 138 402 92 341L111 321C149 368 169 378 178 378C188 378 198 363 214 320L254 212C185 117 138 65 107 65C98 65 85 69 82 75C79 82 73 86 65 86C44 86 23 60 23 39C23 7 44 -12 71 -12C119 -12 168 33 265 177L306 61C321 17 347 -12 373 -12C413 -12 465 33 507 96L491 119C459 84 432 60 413 60C395 60 378 92 358 148L321 250C341 279 369 310 389 332C417 363 439 382 456 382C466 382 475 376 481 368C486 361 492 358 496 358C513 358 536 381 536 404Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,7.202,3.132)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,11.634,3.132)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"></path></g></svg>,</span> and constraint intervals.</div>

Complexity

fig1

Figure 1

Figure 1: Disturbance Observer-Based Adaptive Neural Network Control of Marine Vessel Systems with Time-Varying Output Constraints 