Dynamic Learning from Adaptive Neural Control of Uncertain Robots with Guaranteed Full-State Tracking Precision

<div>Angular position tracking error <svg height="9.14241pt" id="M487" style="vertical-align:-3.1815pt" version="1.1" viewbox="-0.0498162 -5.96091 14.8313 9.14241" width="14.8313pt" 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="M391 364C391 409 353 448 295 448C249 448 198 426 152 393C65 331 23 225 23 139C23 14 96 -12 146 -12C198 -12 280 9 367 101L351 124C300 78 242 48 194 48C129 48 109 107 109 162V191C208 213 391 266 391 364ZM313 350C313 305 268 261 113 223C132 334 187 381 217 398C227 404 244 405 261 405C290 405 313 385 313 350Z" id="g113-102"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="414" vert-adv-y="414" xpluscharwidth="5.382"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,5.317,3.132)"><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" id="g50-50"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="487" vert-adv-y="487" xpluscharwidth="9.74868539"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,9.749,3.132)"><path d="M414 144C384 79 371 75 317 75H135L276 221C367 316 408 376 408 465C408 570 327 635 237 635C179 635 131 609 100 575L42 494L67 471C94 510 138 565 205 565C277 565 321 517 321 435C321 348 258 270 195 195C146 137 88 81 33 26V0H411C423 44 433 88 446 135L414 144Z" id="g50-51"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="487" vert-adv-y="487" xpluscharwidth="14.18068539"></glyph.data></g></svg>: neural learning control (—), ANC (-<svg height="4.18388pt" id="M488" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -4.13406 3.07474 4.18388" width="3.07474pt" 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="M170 255C170 288 146 313 114 313S58 288 58 255C58 221 82 198 114 198S170 221 170 255Z" id="g113-46"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="228" vert-adv-y="228" xpluscharwidth="2.964"></glyph.data></g></svg>-<svg height="4.18388pt" id="M489" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -4.13406 3.07474 4.18388" width="3.07474pt" 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="M170 255C170 288 146 313 114 313S58 288 58 255C58 221 82 198 114 198S170 221 170 255Z" id="g113-46"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="228" vert-adv-y="228" xpluscharwidth="2.964"></glyph.data></g></svg>), and the error bounds (- - -).</div>

Complexity

fig12

Figure 12

Figure 12: Dynamic Learning from Adaptive Neural Control of Uncertain Robots with Guaranteed Full-State Tracking Precision 