This paper proposes a nature inspired, meta-heuristic optimization technique to tune a proportional-integral-derivative (PID) controller for a robotic arm exoskeleton RAX-1. The RAX-1 is a two-degrees-of-freedom (2-DOFs) upper limb rehabilitation robotic system comprising two joints to facilitate shoulder joint movements. The conventional tuning of PID controllers using Ziegler-Nichols produces large overshoots which is not desirable for rehabilitation applications. To address this issue, nature inspired algorithms have recently been proposed to improve the performance of PID controllers. In this study, a 2-DOF PID control system is optimized offline using particle swarm optimization (PSO) and artificial bee colony (ABC). To validate the effectiveness of the proposed ABC-PID method, several simulations were carried out comparing the ABC-PID controller with the PSO-PID and a classical PID controller tuned using the Zeigler-Nichols method. Various investigations, such as determining system performance with respect to maximum overshoot, rise and settling time and using maximum sensitivity function under disturbance, were carried out. The results of the investigations show that the ABC-PID is more robust and outperforms other tuning techniques, and demonstrate the effective response of the proposed technique for a robotic manipulator. Furthermore, the ABC-PID controller is implemented on the hardware setup of RAX-1 and the response during exercise showed minute overshoot with lower rise and settling times compared to PSO and Zeigler-Nichols-based controllers.

STABILIZED CONTROLLER DESIGN FOR ATTITUDE AND ALTITUDE CONTROLLING OF QUAD-ROTOR UNDER DISTURBANCE AND NOISY CONDITIONS

Now a day's Unmanned Aerial Vehicle (UAV) systems are frequently used in many commercial applications. This makes UAV application as one of the hottest topic among the researchers. The most critical task for the researchers working on UAV is its proper and stable flight controlling under uncertainty and perturbed condition. In fixed wing UAV system altitude and attitude angles (Yaw, Pitch, Roll) play a significant role for flight stabilization. This paper presents a control algorithm for fixed-wing UAV longitude and latitude angles (Yaw, Pitch and Roll) controlling. This control algorithm is based on Proportional Integral Derivate (PID) conjunction with Extended Kalman Filter (EKF). It is also describes that how an unstable system become stable after applying proposed control technique. The proposed control method is simulated on fixed-wing UAV mathematical model under perturbed and unperturbed conditions using MATLAB platform. The Simulation results shows that the proposed controller performed well and maintains the stability of an airplane and holds desired angle values under uncertainties and perturbed conditions.

Mobility Assistance Robot (MAR) is a stand stool or an electronic walker. This robot can make a wheelchair bound person to experience the sensation of standing and navigating while standing up. This is not just a wheelchair substitute but indeed an absolutely new and advanced platform of mobility which makes the life of a disabled person easier. It can be controlled by an android mobile phone and users bind or tie themselves into a standing position without any difficulty. This robot can also be controlled through Electromyography (i.e. muscle movement). Electromyography is basically a method of monitoring the motion of neutrons, which are then converted into analog electrical signals and further working is then carried out through these signals. MAR has the potential to carry (lift) the disabled person automatically. It provides a platform for disabled person to ride on it and move with a maximum speed of 10 km/h. The robotic vehicle can be moved in any desired direction using both android mobile application and muscle movement. The person on ride can get the feeling of roaming around like a normal human with legs. This robot is specifically designed to provide a platform for disabled person to live like normal humans. This Robot has many social benefits and caters the need of real world.

Generally Quad-rotor type Unmanned Aerial Vehicles are unstable in nature, so to stabilize it, attitude controller is used. This paper presents a Fuzzy Logic based PID control system (FPID) for attitude stabilization of Quad-rotor Unmanned Aerial Vehicle (UAV). The Fuzzy logic controller updates the PID controller gains efficiently in such a way that it efficiently stabilizes the attitude of quad-rotor UAV. This method enhances the capabilities of conventional PID Controller to a dynamic PID Controller. The propose FPID control technique for attitude controlling of Quad-rotor UAV was tested on developed prototype of Quad rotor UAV for experimental purpose. Experimental results proved that proposed Fuzzy Logic based PID (FPID) controller quickly stabilized Quad-rotor UAV and its response time and settling time is reasonably good in attitude stabilization control application.