This paper introduces an optimal tracking controller for robot manipulators with asymmetrically saturated torques and partially - unknown dynamics based on a reinforcement learning method using neural network. Firstly, the feedforward control inputs are designed backstepping technique to convert problem into problem. Secondly, cost function of system input is defined, constrained Hamilton-Jacob...

Abstract In this paper, a human motion intention estimation-based decentralized robust interaction control method of modular robot manipulators (MRMs) is proposed under the situation physical human–robot (pHRI). Different from traditional scheme that depends on biological signal and centralized method, implemented using only position measurements each joint module in investigation. Based harmon...

Abstract This paper presents a novel compensator-critic structure-based event-triggered decentralized tracking control of modular robot manipulators (MRMs). On the basis subsystem dynamics under joint torque feedback (JTF) technique, proposed error fusion function, which includes position and velocity error, is utilized to construct performance index function. By analyzing dynamic uncertainties...

This paper considers the power capture control problem of variable-speed wind turbine (VSWT) systems with flexible shaft. The objective is to optimize energy by tracking desired output. A novel command filter based adaptive signal feedback (PSF) method proposed design PSF controller for non-affine nonlinear VSWT a two-mass model which parameters are totally unknown. compensation dynamic adaptab...

This paper addresses the distributed optimal decoupling synchronous control of multiple autonomous unmanned linear systems (MAUS) subject to complex network dynamic coupling. The leader–follower mechanism based on neighborhood error dynamics is established and coupling term regarded as external disturbance realize cooperative each agent. Bounded L2-Gain problem for formulated into a multi-playe...

In this paper, an event-triggered Reinforcement Learning (RL) method is proposed for the optimal attitude consensus of multiple rigid body networks with unknown dynamics. Firstly, error constructed through According to Bellman optimality principle, implicit form controller and corresponding Hamilton-Jacobi-Bellman (HJB) equations are obtained. Because augmented system, can be obtained directly ...

In this paper, an event-triggered adaptive dynamic programming (ADP) method is proposed to deal with the H∞ problem unknown and constrained input. Firstly, H∞-constrained regarded as two-player zero-sum game nonquadratic value function. Secondly, we develop Hamilton–Jacobi–Isaacs(HJI) equation, ADP solve HJI which equivalent solving Nash saddle point of game. An event-based single-critic neural...

با توجه به الزامات زیست‌محیطی، اجتماعی و اقتصادی، طراحی شبکه زنجیره تأمین حلقه‌­بسته پژوهشگران زیادی را خود جذب کرده است. این مسئله بیشتر به‌صورت مجزا از ارزیابی تأمین‌کنندگان موردمطالعه قرار گرفته عوامل مختلفی به‌جز قیمت مانند ویژگی‌های تأمین‌کننده قطعه می‌تواند تأثیر بر عملکرد داشته باشد. در پژوهش یک شامل سایت‌های تولید، جداسازی، بازسازی دفع نظر مدلی تلفیقی سه مرحله ارائه شده نخست روش ترکیبی ...

عصاره گیاه رزماری، 4 برابر آنتی­اکسیدان‌­های مصنوعی مانند BHT و BHA خاصیت آنتی­اکسیدانی دارد. رزمارینیک اسید نه تنها به دلیل خواص قوی مورد توجه است بلکه خصوصیات ضدالتهابی، ضدتوموری، ضدباکتریایی، ضدویروسی ضدسرطانی را نیز در پژوهش‌­های مختلف نشان داده است. هدف از این تحقیق، بررسی اثرات دما، زمان، pH غلظت پرتودیده نشان‌دارسازی آن با رادیوایزوتوپ گالیم-67 عنوان یک عامل تصویربرداری وضوح بالا برای تو...

The planning of whole-body motion and step time for bipedal locomotion is constructed as a model predictive control (MPC) problem, in which sequence optimization problems needs to be solved online. While directly solving these extremely time-consuming, we propose gait synthesizer offer immediate solutions. Based on the full-dimensional model, library gaits with different speeds periods first of...