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Lateral and torsional vibrations of a robot manipulator with an elastic arm sliding in a prismatic joint are analyzed. The elastic arm is assumed as an Euler-Bernoulli beam. The mass of the end-effector is assumed as a point mass attached at the end of the elastic arm. The prismatic joint experiences 3-dimensional translational and rotational motion. The prismatic joint is assumed as rigid and frictionless. Rotational inertia of the beam is taken into consideration in obtaining the equations of motion. Elastic deformations are assumed as linear and small displacements. Axial vibrations are not considered but the effect of axial force is taken into account in the analysis. Elastic arm experiences both bending vibrations in two directions and torsional vibrations. The equations of motion are obtained by Lagrange’s equation of motion. Numerical solution of the equations of motion are obtained by Runge-Kutta method. A computer program is developed for implementation of the presented technique. Numerical simulations are presented in the form of graphics. Presented method is found to be versatile in dynamic analysis of elastic robot arms.

In this study, interval type2 fuzzy logic (IT2FL) and PID controller is designed for swing-up position control of double inverted pendulum (DIP) system. The double inverted pendulum system consists of two rigid bars connected by a revolute joint. Mass of the revolute joint is included in the dynamic model.Rigid bars in the system are assumed to experience planar motion. The pendulum system is connected to the base by means of a revolute joint. Torque provided through a motor mounted to the base is used for position control of the system. PID (Proportional-Derivative-Integral) and interval type2 fuzzy logic controllers are developed by using the same performance criteria for position control of double inverted pendulum system. IT2FL controller is similar with type1 fuzzy logic controller. IT2FL system provides soft decision boundaries, whereas a type-1 fuzzy logic system provides a hard decision boundary. Membership function in interval type2 fuzzy logic set as an area called Footprint of Uncertainty (FOU) which limited by two type1 membership function those are upper membership function (UMF) and lower membership function (LMF).System behaviour is obtained by computer simulation using developed controllers respectively. Computer simulation results are compared in order to evaluate applicability of developed controllers. MATLAB/Simulink software is used in computer simulations.

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Lower extremity exoskeletons are wearable robot manipulators that integrate human intelligence with the strength of legged robots. Recently, lower extremity exoskeletons have been specifically developed for rehabilitation, military, industrial applications and rescuing, heavy-weight lifting and civil defense applications. This paper presents controller design of a lower-extremity exoskeleton for a load carrying human to provide force feedback control against to external load carried by user during walking, sitting, and standing motions. Proposed exoskeleton system has two legs which are powered and controlled by two servo-hydraulic actuators. Proportional and Integral (PI) controller is designed for force control of system. Six flexible force sensors are placed in exoskeleton shoe and two load cells are mounted between the end of the piston rod and lower leg joint. Force feedback control is realized by comparing ground reaction force and applied force of hydraulic cylinder. This paper discusses control simulations and experimental tests of lower extremity exoskeleton system.