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Yu, "Toward integrating feature selection algorithms for classification and clustering," IEEE Transactions on Knowledge & Data Engineering, pp. 491-502, 2005.mortezavaseghyaghoubpourasad1021202016917510.66224/jict.13603.12.43.169http://jour.aicti.ir/en/Article/13603http://jour.aicti.ir/en/Article/Download/13603http://jour.aicti.ir/en/Article/Download/13603http://jour.aicti.ir/en/Article/Download/13603http://jour.aicti.ir/en/Article/Download/13603http://jour.aicti.ir/en/Article/Download/13603http://jour.aicti.ir/en/Article/Download/13603http://jour.aicti.ir/en/Article/Download/13603با پیشرفت علوم و صنایع و اهمیت به کارگیری ربات‌ها، ضرورت استفاده از سیستم‌های خودکار امری ضروری به نظر می‌رسد. از آنجا که بیشتر کاربردهای ربات‌های مار حرکت در محیط‌های ناشناخته و بعضاً پیچیده است، لزوم ایجاد روش‌های کنترلی متفاوت برای آن‌ها احساس می‌شود. ماحصل ادغام دو علم عصب شناسی و رباتیک، تولید کننده‌های عصبی حرکتی هستند که با نام مولدهای مرکزی الگو شناخته می‌شوند که مسئله تولید حرکت در ربات می‌باشد. در این مقاله به بررسی کنترل حرکت ربات مار مانند با مولد مرکزی الگو (CPG) پرداخته شده که قادر به تولید الگوهای هماهنگ سیگنال‌های خروجی با فرکانس‌های مختلف هستند، بدین منظور لازم است که در ابتدا ربات مار مدل شود و پس از آن اعمال کنترلی اعمال شود. در این مقاله بررسی کنترل حرکت ربات در دو حالت حلقه باز و حلقه بسته برای شبکه CPG ارائه شده است. در عین حال این پژوهش با شبیه‌سازی‌های انجام شده نشان می‌دهد که هر چه میزان تحریک کمتر باشد و سطح آن پایین‌تر، منجر به تولید حرکتی با فرکانس پایین‌تر می‌شود و بالعکس. سپس نحوه تاثیر مدل‌های CPG که به عنوان شبکه‌های عصبی استفاده می‌شوند، در کنترل حرکت شبیه‌سازی شده‌اند. در این مقاله نکته قابل توجه در مقایسه با سایر کنترل کننده‌ها این است که در شبکه‌های عصبی مولد مرکزی الگو سیگنال‌های ساده برای تحریک و القای حرکت ربات‌ها کافی می‌باشد که در شبیه‌سازی نشان داده شده است.