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Author: Israa Taqa Publisher: LAP Lambert Academic Publishing ISBN: 9783659575785 Category : Languages : en Pages : 168
Book Description
The emergence of computational intelligence technology inspired by biological and human intelligence is one of the most exciting and important fields in engineering . It is expected that these technologies like fuzzy logic, will play a significant role in the development of intelligent robotic systems, machine systems, and mechatronics systems . In this work; a Fuzzy Logic Controller is presented to control the motion of a robotic arm and avoid the obstacles existed in its mission road, using a real platform robotic arm in combination with a vision system . This work involves constructing an integrated and autonomic MATLAB program. It could be applicable for any robotic arm . It depends on a new approach in analyzing the robotic environment videos acquired by a fixed webcam. The approach uses colors to detect and recognize the changeable locations and objects' dimensions for each of the robot's end-effector, the goal, and the obstacles .
Author: Israa Taqa Publisher: LAP Lambert Academic Publishing ISBN: 9783659575785 Category : Languages : en Pages : 168
Book Description
The emergence of computational intelligence technology inspired by biological and human intelligence is one of the most exciting and important fields in engineering . It is expected that these technologies like fuzzy logic, will play a significant role in the development of intelligent robotic systems, machine systems, and mechatronics systems . In this work; a Fuzzy Logic Controller is presented to control the motion of a robotic arm and avoid the obstacles existed in its mission road, using a real platform robotic arm in combination with a vision system . This work involves constructing an integrated and autonomic MATLAB program. It could be applicable for any robotic arm . It depends on a new approach in analyzing the robotic environment videos acquired by a fixed webcam. The approach uses colors to detect and recognize the changeable locations and objects' dimensions for each of the robot's end-effector, the goal, and the obstacles .
Author: Mohamed Al-Mahdi Eshtawie Publisher: ISBN: Category : Fuzzy logic Languages : en Pages : 320
Book Description
During the past several years fuzzy logic control (FLC) has emerged as one of the most active and fruitful areas for research in the application of intelligent system design. Presently, fufzy logic has found a variety of applications in various fields ranging from industrial pro~ess control to medical diagnosis and securities trading. Most notably, a fuzzy logic system has been applied to control nonlinear, time-varying, ill-defined systems, to control systems whose dynamics are not exactly known, as servomotors position control, and robot arm control, and to manage complex decision-making or diagnostic systems. This project has the objective of designing a fuzzy logic controller, which will be used to control the navigation process of an autonomous mobile robot in a completely unstructured environment. The navigation algorithm is proposed for static obstacles and with no priori knowledge about the environment. In addition, an on-line path planning is used while navigation. The controller will have its inputs from the sensors that will be mounted on the robot. The number of sensors used is five where, three of them will be on the front side of the robot, whereas, one on the left side and one on the right side. The FLC was designed using three different fuzzifiers (triangular, trapezoidal and Gaussian) to represent the sensor readings values so that they can be interpreted by the inference mechanism. Moreover, two different implication methods (Mamdani minimum and Mamdani Product) implications are used in the interpretation of the IF-THEN rules in the rule-base. Depending on the number of fuzzy sets used to represent the sensor readings, the total number of control rules used in the design was 243 at the first stage and then reduced to 108. In other words, if the number of fuzzy sets used to represent each sensor reading is three (far, near, and very near) then the total number of rules is 243 which is (~5). On the other hand, if the left and right sensors reading values were represented using only two fuzzy sets (far and near) then the total number of rules is 108 i.e. (33 *22). In addition, two defuzzification 'strategies (center of gravity and center average) were used to get the output of the FLC in a crisp value. It was observed that the triangular fuzzifier, center average defuzzification method, and the Mamdani minimum implication method with a total number of 108 rule are the best choices for the design.
Author: Mahmut Dirik Publisher: Springer Nature ISBN: 3030692477 Category : Technology & Engineering Languages : en Pages : 143
Book Description
The book includes topics, such as: path planning, avoiding obstacles, following the path, go-to-goal control, localization, and visual-based motion control. The theoretical concepts are illustrated with a developed control architecture with soft computing and artificial intelligence methods. The proposed vision-based motion control strategy involves three stages. The first stage consists of the overhead camera calibration and the configuration of the working environment. The second stage consists of a path planning strategy using several traditional path planning algorithms and proposed planning algorithm. The third stage consists of the path tracking process using previously developed Gauss and Decision Tree control approaches and the proposed Type-1 and Type-2 controllers. Two kinematic structures are utilized to acquire the input values of controllers. These are Triangle Shape-Based Controller Design, which was previously developed and Distance-Based Triangle Structure that is used for the first time in conducted experiments. Four different control algorithms, Type-1 fuzzy logic, Type-2 Fuzzy Logic, Decision Tree Control, and Gaussian Control have been used in overall system design. The developed system includes several modules that simplify characterizing the motion control of the robot and ensure that it maintains a safe distance without colliding with any obstacles on the way to the target. The topics of the book are extremely relevant in many areas of research, as well as in education in courses in computer science, electrical and mechanical engineering and in mathematics at the graduate and undergraduate levels.
Author: Viorel Stoian Publisher: ISBN: 9789537619176 Category : Languages : en Pages :
Book Description
The section 3 presents a new control method for mobile robots moving in its work field which is based on fuzzy logic and artificial potential field. First, the artificial potential field method is presented. The section treats unconstrained movement based on attractive artificial potential field and after that discuss the constrained movement based on attractive and repulsive artificial potential field. A fuzzy controller is designed. Finally, some applications are presented. The section 4 presents a fuzzy control algorithm for mobile robots which are moving next to the obstacle boundaries, avoiding the collisions with them. Four motion cycles (programs) depending on the proximity levels and followed by the mobile robot on the trajectory (P1, P2, P3, and P4) are shown. The directions of the movements corresponding to every cycle, for every reached proximity level are presented. The sequence of the programs depending on the reached proximity levels is indicated. The motion control algorithm is presented by a flowchart showing the evolution of the functional cycles (programs). The fuzzy rules for evolution (transition) of the programs and for the motion on X-axis and Y-axis respectively are described. The fuzzy controller for the mobile robots based on the algorithm presented above is simple. Finally, some simulations are presented. If the object is like a circle, every program is proper for a quarter of the circle.
Author: Xiaoqing Ma Publisher: ISBN: Category : Fuzzy algorithms Languages : en Pages : 0
Book Description
Control of under-actuated mechanical systems (robots) represents an important class of control problem. This thesis studies several related control problems associated with an under-actuated robot, Pendubot, from the point view of fuzzy logic control. To swing up the Pendubot from a rest position to the upright configuration, a fuzzy algorithm is proposed from non-complete sets of linguistic rules that link some mechanism states to the sign of a single control action. Therein, a simplified Tsukamoto's reasoning method and quasi-linear-mean aggregating operators are used to derive and analyze the controller input-out mappings. In order to balance the Pendubot at the unstable upright top configuration after swinging up, another simple fuzzy controller is derived according to its joint states: This combining fuzzy algorithm for swinging-up and balancing is successfully applied to the Pendubot. This thesis also investigates the case that the Pendubot tracks a desired signal and a corresponding fuzzy scheme is proposed, which combines the linear regulator theory with the Takagi-Sugeno fuzzy methodology. The stability and stability conditions for this fuzzy scheme are analyzed. Numerical simulations for all the above controllers are carried out to validate the theoretical analysis by using SIMULINK. Finally, the hardware experiments in the Pendubot have successfully been conducted in the Robotics and Mechatronics Laboratory.
Author: Israa Taqa
Author: Israa Taqa
Author: Mohamed Al-Mahdi Eshtawie
Author: Beheshteh Hajmahmoudsayeh
Author: Mahmut Dirik
Author: Kong Chu
Author: Martin Soucy
Author: Eddie Kwan
Author: 
Author: Viorel Stoian
Author: Xiaoqing Ma