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Go to Editorial ManagerThis paper presents a novel control framework for robot manipulator path tracking based on the integration of artificial immune systems, fuzzy logic, and fractional-order PID control. The proposed Fuzzy-Immune Fractional-Order PID (FIFOPID) controller combines immune feedback mechanisms, fuzzy logic reasoning, and fractional-order control principles, with controller parameters optimized using the Clonal Selection Algorithm (CSA). The performance of the FIFOPID controller is evaluated and compared against a Fuzzy-Immune PID (FIPID) controller under identical conditions. Simulation results conducted in MATLAB 2014a with SIMULINK demonstrate that the optimal FIFOPID controller outperforms the FIPID controller in terms of path tracking accuracy and overall control performance, highlighting its potential as an effective approach for precise robotic manipulator control.
The Mobile Manipulator Robot (MMR) has many applications in different aspects of the life, for example, grasping and transporting, mining, military, manufacturing, construction and others. The benefits of MMR rise in dangerous place where the human cannot reach such as disaster areas and dangerous projects sites. In this work, the PID controller is combined with Fuzzy Logic Controller (FLC) to structure the Fuzzy Supervisory Controller (FSC) to overcome the drawbacks of PID controller and to obtain the advantages of FLC. Two approaches are suggested for the navigation of Autonomous Mobile Robot (AMR). These are; goal reaching fuzzy control (GRFC) and the obstacle avoidance fuzzy control (OAFC). The hardware implementation of the AMR is performed using AVR ATmega32 microcontroller, two DC motors, light dependent resistor (LDR) and five Infra Red sensors. While, the Laboratory robot arm with some fabrications is used as manipulator arm with a five degrees-of- freedom. Then a microcontroller is employed to implement the proposed controller for MMR. The designed MMR is tested in real environments and give a good navigation.