دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — بخش سیزدهم

منطق فازی (Fuzzy Logic) اولین بار در پی تنظیم نظریه مجموعه‌های فازی به وسیله پروفسور لطفی زاده (۱۹۶۵ میلادی) در صحنه محاسبات نو ظاهر شد. در واقع منطق فازی از منطق ارزش‌های «صفر و یک» نرم‌افزارهای کلاسیک فراتر رفته و درگاهی جدید برای دنیای علوم نرم‌افزاری و رایانه‌ها می‌گشاید، زیرا فضای شناور و نامحدود بین اعداد صفر و یک را نیز در منطق و استدلال‌های خود به کار می‌گیرد. در ادامه مقالات علمی انتشارات بین المللی اشپرینگر (Springer) در زمینه منطق فازی (Fuzzy Logic) برای دانلود آمده است. می توانید برای دانلود هر یک از مقالات از سرور دانلود متلب سایت، بر روی لینک دانلود هر یک از آن ها، کلیک کنید.

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دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — فهرست اصلی

عنوان اصلی مقاله Type-2 Fuzzy Control for a Flexible- joint Robot Using Voltage Control Strategy
نوع مقاله مقاله ژورنال
نویسندگان Majid Moradi Zirkohi, Mohammad Mehdi Fateh, Mahdi Aliyari Shoorehdeli
چکیده / توضیح Type-1 fuzzy sets cannot fully handle the uncertainties. To overcome the problem, type-2 fuzzy sets have been proposed. The novelty of this paper is using interval type-2 fuzzy logic controller (IT2FLC) to control a flexible-joint robot with voltage control strategy. In order to take into account the whole robotic system including the dynamics of actuators and the robot manipulator, the voltages of motors are used as inputs of the system. To highlight the capabilities of the control system, a flexible joint robot which is highly nonlinear, heavily coupled and uncertain is used. In addition, to improve the control performance, the parameters of the primary membership functions of IT2FLC are optimized using particle swarm optimization (PSO). A comparative study between the proposed IT2FLC and type-1 fuzzy logic controller (T1FLC) is presented to better assess their respective performance in presence of external disturbance and unmodelled dynamics. Stability analysis is presented and the effectiveness of the proposed control approach is demonstrated by simulations using a two-link flexible-joint robot driven by permanent magnet direct current motors. Simulation results show the superiority of the IT2FLC over the T1FLC in terms of accuracy, robustness and interpretability.
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عنوان اصلی مقاله Observer-based Adaptive Fuzzy Control for a Class of Nonlinear Time-delay Systems
نوع مقاله مقاله ژورنال
نویسندگان Hassan A. Yousef, Mohamed Hamdy
چکیده / توضیح An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach.
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عنوان اصلی مقاله Adaptive Fuzzy Sliding Mode Power System Stabilizer Using Nussbaum Gain
نوع مقاله مقاله ژورنال
نویسندگان Emira Nechadi, Mohamed Naguib Harmas, Najib Essounbouli, Abdelaziz Hamzaoui
چکیده / توضیح Power system stability is enhanced through a novel stabilizer developed around an adaptive fuzzy sliding mode approach which applies the Nussbaum gain to a nonlinear model of a single-machine infinite-bus (SMIB) and multi-machine power system stabilizer subjected to a three phase fault. The Nussbaum gain is used to avoid the positive sign constraint and the problem of controllability of the system. A comparative simulation study is presented to evaluate the achieved performance.
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عنوان اصلی مقاله ANFIS-based Sensor Fusion System of Sit- to- stand for Elderly People Assistive Device Protocols
نوع مقاله مقاله ژورنال
نویسندگان Omar Salah, Ahmed A. Ramadan, Salvatore Sessa, Ahmed Abo Ismail, Makasatsu Fujie, Atsuo Takanishi
چکیده / توضیح This paper describes the analysis and design of an assistive device for elderly people under development at the Egypt-Japan University of Science and Technology (E-JUST) named E-JUST assistive device (EJAD). Several experiments were carried out using a motion capture system (VICON) and inertial sensors to identify the human posture during the sit-to-stand motion. The EJAD uses only two inertial measurement units (IMUs) fused through an adaptive neuro-fuzzy inference systems (ANFIS) algorithm to imitate the real motion of the caregiver. The EJAD consists of two main parts, a robot arm and an active walker. The robot arm is a 2-degree-of-freedom (2-DOF) planar manipulator. In addition, a back support with a passive joint is used to support the patient’s back. The IMUs on the leg and trunk of the patient are used to compensate for and adapt to the EJAD system motion depending on the obtained patient posture. The ANFIS algorithm is used to train the fuzzy system that converts the IMUs signals to the right posture of the patient. A control scheme is proposed to control the system motion based on practical measurements taken from the experiments. A computer simulation showed a relatively good performance of the EJAD in assisting the patient.
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عنوان اصلی مقاله Real-time compliance control of an assistive joint using QNX operating system
نوع مقاله مقاله ژورنال
نویسندگان Shuang Gu, Cheng-Dong Wu, Yong Yue, Carsten Maple, Da-You Li, Bei-Sheng Liu
چکیده / توضیح An assistive robot is a novel service robot, playing an important role in the society. For instance, it can amplify human power not only for the elderly and disabled to recover/rehabilitate their lost/impaired musculoskeletal functions but also for healthy people to perform tasks requiring large forces. Consequently, it is required to consider both accurate position control and human safety, which is the compliance. This paper deals with the robot control compliance problem based on the QNX real-time operating system. Firstly, the mechanical structure of a compliant joint on the assistive robot is designed using Solidworks. Then the parameters of the assistive robot system are identified. The software of robot control includes data acquisition and processing, and control to meet the compliance requirement of the joint control. Finally, a Hogan impedance control experiment is carried out. The experimental results prove the effectiveness of the method proposed.
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عنوان اصلی مقاله Dynamics and Control of a Novel 3 -DOF Parallel Manipulator with Actuation Redundancy
نوع مقاله مقاله ژورنال
نویسندگان Xue-Mei Niu, Guo-Qin Gao, Xin-Jun Liu, Zhi-Da Bao
چکیده / توضیح This paper deals with the dynamics and control of a novel 3-degrees-of-freedom (DOF) parallel manipulator with actuation redundancy. According to the kinematics of the redundant manipulator, the inverse dynamic equation is formulated in the task space by using the Lagrangian formalism, and the driving force is optimized by utilizing the minimal 2-norm method. Based on the dynamic model, a synchronized sliding mode control scheme based on contour error is proposed to implement accurate motion tracking control. Additionally, an adaptive method is introduced to approximate the lumped uncertainty of the system and provide a chattering-free control. The simulation results indicate the effectiveness of the proposed approaches and demonstrate the satisfactory tracking performance compared to the conventional controller in the presence of the parameter uncertainties and un-modelled dynamics for the motion control of manipulators.
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عنوان اصلی مقاله An Integrated Approach to Hypersonic Entry Attitude Control
نوع مقاله مقاله ژورنال
نویسندگان Zhi-Qiang Pu, Ru-Yi Yuan, Xiang-Min Tan, Jian-Qiang Yi
چکیده / توضیح This paper presents an integrated approach based on dynamic inversion (DI) and active disturbance rejection control (ADRC) to the entry attitude control of a generic hypersonic vehicle (GHV). DI is firstly used to cancel the nonlinearities of the GHV entry model to construct a basic attitude controller. To enhance the control performance and system robustness to inevitable disturbances, ADRC techniques, including the arranged transient process (ATP), nonlinear feedback (NF), and most importantly the extended state observer (ESO), are integrated with the basic DI controller. As one primary task, the stability and estimation error of the second-order nonlinear ESO are analyzed from a brand new perspective: the nonlinear ESO is treated as a specific form of forced Liénard system. Abundant qualitative properties of the Liénard system are utilized to yield comprehensive theorems on nonlinear ESO solution behaviors, such as the boundedness, convergence, and existence of periodic solutions. Phase portraits of ESO estimation error dynamics are given to validate our analysis. At last, three groups of simulations, including comparative simulations with modeling errors, Monte Carlo runs with parametric uncertainties, and a six degrees-of-freedom reference entry trajectory tracking are executed, which demonstrate the superiority of the proposed integrated controller over the basic DI controller.
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عنوان اصلی مقاله A Modeling and Probabilistic Reasoning Method of Dynamic Uncertain Causality Graph for Industrial Fault Diagnosis
نوع مقاله مقاله ژورنال
نویسندگان Chun-Ling Dong, Qin Zhang, Shi-Chao Geng
چکیده / توضیح Online automatic fault diagnosis in industrial systems is essential for guaranteeing safe, reliable and efficient operations. However, difficulties associated with computational overload, ubiquitous uncertainties and insufficient fault samples hamper the engineering application of intelligent fault diagnosis technology. Geared towards the settlement of these problems, this paper introduces the method of dynamic uncertain causality graph, which is a new attempt to model complex behaviors of real-world systems under uncertainties. The visual representation to causality pathways and self-relied “chaining” inference mechanisms are analyzed. In particular, some solutions are investigated for the diagnostic reasoning algorithm to aim at reducing its computational complexity and improving the robustness to potential losses and imprecisions in observations. To evaluate the effectiveness and performance of this method, experiments are conducted using both synthetic calculation cases and generator faults of a nuclear power plant. The results manifest the high diagnostic accuracy and efficiency, suggesting its practical significance in large-scale industrial applications.
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عنوان اصلی مقاله Improving Asynchronous Motor Speed and Flux Loop Control by Using Hybrid Fuzzy-SMC Controllers
نوع مقاله مقاله ژورنال
نویسندگان Ismail Bendaas, Farid Naceri, Sebti Belkacem
چکیده / توضیح This paper presents a new method combining sliding mode control (SMC) and fuzzy logic control (FLC) to enhance the robustness and performance for a class of non-linear control systems. This fuzzy sliding mode control (FSMC) is developed for application in the area for controlling the speed and flux loops of asynchronous motors. The proposed control law can solve those problems associated with the conventional control by sliding mode control, such as high current, flux and torque chattering, variable switching frequency and variation of parameters, in which a robust fuzzy logic controller replaces the discontinuous part of the classical sliding mode control law. Simulation results of the proposed FSMC technique on the speed and flux rotor controllers present good dynamic and steady-state performances compared to the classical SMC in terms of reduction of the torque chattering, quick dynamic torque response and robustness to disturbance and variation of parameters.
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عنوان اصلی مقاله An Improved Gravitational Search Algorithm for Dynamic Neural Network Identification
نوع مقاله مقاله ژورنال
نویسندگان Bao-Chang Xu, Ying-Ying Zhang
چکیده / توضیح Gravitational search algorithm (GSA) is a newly developed and promising algorithm based on the law of gravity and interaction between masses. This paper proposes an improved gravitational search algorithm (IGSA) to improve the performance of the GSA, and first applies it to the field of dynamic neural network identification. The IGSA uses trial-and-error method to update the optimal agent during the whole search process. And in the late period of the search, it changes the orbit of the poor agent and searches the optimal agent’s position further using the coordinate descent method. For the experimental verification of the proposed algorithm, both GSA and IGSA are testified on a suite of four well-known benchmark functions and their complexities are compared. It is shown that IGSA has much better efficiency, optimization precision, convergence rate and robustness than GSA. Thereafter, the IGSA is applied to the nonlinear autoregressive exogenous (NARX) recurrent neural network identification for a magnetic levitation system. Compared with the system identification based on gravitational search algorithm neural network (GSANN) and other conventional methods like BPNN and GANN, the proposed algorithm shows the best performance.
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