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In this paper, fuzzy logic velocity control of a biped robot to generate gait is studied. The system considered in this study has six degrees of freedom with hip, knee and ankle joints. The joint angular positions are determined utilizing the Cartesian coordinate information of the joints obtained by using camera captured data of the motion. The first derivatives of the calculated joint angular positions are applied as the reference angular velocity input to the fuzzy controllers of the joint servomotors to generate a gait motion. The assumed motion for the biped robot is horizontal walking on a flat surface. The actuated joints are hip, knee and ankle joints which are driven by DC servomotors. The calculated angular velocities of the joints from camera captured motion data are utilized to get the driving velocity functions of the model as sine functions. These functions are applied to the fuzzy controller as the reference angular velocity inputs. The control signals produced by the fuzzy controllers are applied to the servomotors and then the response of the servomotor block is introduced as an input to the SimMechanics model of the biped robot. The simulation results are provided which evaluate the effectiveness of the fuzzy logic controller on joint velocities to generate gait motion.

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A hybrid learning procedure referred to as adaptive neuro fuzzy inference system (ANFIS) is applied to an artificial leg model to generate the correct positions of the servomotors actuating the leg joints. One of the most important control problems of mechanical arms and legs is the efficient calculation of correct joint angles for a space trajectory. Although this application represents the simplest model with two degrees of freedom, the practicality of ANFIS for such mechanical systems is validated. For the gait model of the proposed mechanism, the experimental planar motion of the ankle joint is transformed to joint angles by ANFIS and approximated by polynomial functions. The corresponding servomotor positions are obtained by the proposed inverse kinematic solution method and are included in a Simulink model as an embedded Matlab function. A hybrid control system consisting of combination of a proportional plus derivative (PD) controller and a fuzzy logic controller (FLC) is applied to control the selected servomotors. The accuracy of the control system is further verified on SimMechanics.

In this study, the equation of motion of a single link flexible robotic arm with end mass, which is driven by a flexible shaft, is obtained by using Hamilton's principle. The physical system is considered as a continuous system. As a first step, the kinetic energy and the potential energy terms and the term for work done by the nonconservative forces are established. Applying Hamilton's principle the variations are calculated and the time integral is constructed. After a series of mathematical manipulations the coupled equations of motion of the physical system and the related boundary conditions are obtained. Numerical solutions of equations of motion are obtained and discussed for verification of the model used.