The Adaptive Neural Control for a Class of High-Order Uncertain Stochastic Nonlinear Systems

<div>The responses of the adaptive law <svg height="12.1306pt" id="M296" style="vertical-align:-0.2063999pt" version="1.1" viewbox="-0.0498162 -11.9242 9.74267 12.1306" width="9.74267pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,.528,-2.897)"><path d="M658 557C549 593 437 629 340 673H318C222 629 109 593 0 557L9 532C116 551 225 577 329 602C435 576 543 551 649 532L658 557Z" id="g119-105"></path></g><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M377 665C166 665 44 494 44 317C44 126 183 -15 363 -15C547 -15 695 118 695 333C695 533 546 665 377 665ZM355 630C491 630 593 515 593 304C593 112 496 22 385 22C245 22 146 157 146 345S244 630 355 630ZM502 225V442H471C464 375 459 369 411 369H326C278 368 273 374 266 442H235V225H266C273 292 278 299 326 299H411C459 299 464 292 471 225H502Z" id="g113-137"></path></g></svg> and the controller <svg height="6.1673pt" id="M297" style="vertical-align:-0.2063904pt" version="1.1" viewbox="-0.0498162 -5.96091 7.11985 6.1673" width="7.11985pt" 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="M515 96L502 119C471 88 431 62 423 62C416 62 411 70 417 101C440 223 469 341 497 448H486L412 422L380 277C330 188 210 57 152 57C137 57 126 69 139 124L195 366C210 431 205 448 182 448C155 448 89 413 23 350L36 326C73 354 103 376 112 376C118 376 118 365 113 340L61 118C54 90 52 68 52 51C52 0 75 -12 98 -12S151 -3 181 17C242 58 305 119 362 193H364L345 104C323 3 339 -12 359 -12C390 -12 464 35 515 96Z" id="g113-118"></path></g></svg> relative to time.</div>

Mathematical Problems in Engineering

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Figure 2

Figure 2: The Adaptive Neural Control for a Class of High-Order Uncertain Stochastic Nonlinear Systems 