Mete Kalyoncu

Design and Actuator Selection of a Lower Extremity Exoskeleton

Lower extremity exoskeletons are wearable robots that integrate human intelligence with the strength of legged robots. Recently, lower extremity exoskeletons have been specifically developed for transportation of disabled individuals. This paper summarizes the anthropomorphic design of a lower extremity exoskeleton named “walking supporting exoskeleton (WSE).” WSE has been developed to support some fundamental motions (walking, sitting, standing, etc.) of disabled individuals who lost leg muscular activities completely or partially. WSE has two degrees of freedom per leg which are powered by electrical actuators. This paper discusses critical design criteria considered in mechanical design and actuator selection of WSE.

Optimisation of a fuzzy logic controller for a flexible single-link robot arm using the Bees Algorithm

This paper focuses on using the Bees Algorithm to tune the scaling gains and other parameters of a fuzzy logic controller for a flexible single-link robot arm. The algorithm optimises those quantities so that the controller can move the link to a desired position with the minimum amount of vibration during the movement. Following a description of the algorithm, the paper gives the experimental results obtained for the robot demonstrating the efficiency and robustness of the design.

Automatic design of control systems for robot manipulators using the bees algorithm

This paper proves the capability of the bees algorithm to solve complex parameter optimization problems for robot manipulator control. Two applications are presented. The first case considers the modelling of the inverse kinematics of an articulated robot arm using neural networks. The weights of the connections between the nodes need to be set so as to minimize the difference between the neural network model and the desired behaviour. In the proposed example, the bees algorithm is used to train three multilayer perceptrons to learn the inverse kinematics of the joints of a three-link manipulator. The second case considers the design of a hierarchical proportional–integral–derivative (PID) controller for a flexible single-link robot manipulator. The six gains of the PID controller need to be optimized so as to minimize positional inaccuracies and vibrations. Experimental tests demonstrated the validity of the proposed approach. In the first case, the bees algorithm proved very effective at optimizing the neural network models. Compared with the results obtained employing the standard back-propagation rule and an evolutionary algorithm, the bees algorithm obtained superior results in terms of training accuracy and robustness. In the second case, the proposed method demonstrated remarkable efficiency and consistency in the tuning of the PID controller parameters. In 50 independent optimization trials, the PID controllers designed using the bees algorithm consistently outperformed a robot controller designed using a standard manual technique.

Pid and interval type-2 fuzzy logic control of double inverted pendulum system

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.

Fuzzy logic trajectory control of flexible robot manipulator with rotating prismatic joint

In this study, a fuzzy logic controller is designed in order to use in trajectory control of a robot manipulator. The considered robot manipulator consists of a rotating-prismatic joint housing a sliding flexible arm that carries a concentrated mass at the tip end. The tip end of the flexible arm traces a multi-straight-line path. This study is aimed to use a fuzzy logic controller in controlling the trajectory traced by the tip end of the flexible arm so as to reduce the vibrations induced in the flexible arm. The designed fuzzy controller is aimed to control both the position of the tip end of the flexible robot arm while the tip end traces a multi-straight-line path and the vibrations induced in the flexible arm. Numerical simulations obtained by using a developed computer program are presented and physical trend of obtained numerical results are discussed. The performance of the fuzzy logic control system is evaluated on the basis of the simulation results.

Mathematical Modeling and Simulation of a Flexible Shaft-Flexible Link System With End Mass

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 Hamiltons 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 Hamiltons 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.

Adaptive network based fuzzy logic control of a rigid - flexible robot manipulator

In this study position and vibration control of a rigid-flexible robot manipulator is investigated. Initially dynamic model of the manipulator system is obtained by using Lagrange equations and assumed modes method. Two adaptive networks based fuzzy logic controllers (ANFLCs) are proposed for tracking control of the rigid link and the flexible link. The training and testing data of ANFLCs are obtained from the conventional PD control of the manipulator system. The performances of ANFLCs are tested for different type and different number of membership functions. Finally simulation results are obtained. Results demonstrate the remarkable performance of the proposed controllers.

Modelling and Controller Design for a Flexible Structure System against Disturbance Effects

The effects of natural hazards such as earthquakes are serious threat to structures and most researchers have studied structural control systems. Vibration and displacement control of structures under seismic excitation are important problems for which a solution is to use structural control against the disturbances. This paper presents modelling and controller design for flexible structure systems against unexpected disturbance effects such as seismic excitation. The proposed system consists of two flexible floors with active mass damper. The system is set up on a shake-table and disturbances are created by the shake-table. Active mass damper consists of a moving mass actuated by a servomotor, which moves linearly and is mounted on the second floor to suppress structural vibrations and displacements. In simulation works, different types of modeling technique are used to obtain dynamic behaviour of the proposed system and control of the simulated system is carried out using SolidWorks and MATLAB/SimMechanics. Moreover linear quadratic regulator and proportional-integral-derivative controllers are designed to control the moving mass in active mode while the system is under excitation. For this purpose a full-order observer is formed and implemented as control strategy. Furthermore acceleration and displacement responses of the floors and displacement of proportional velocity controlled cart are investigated in passive mode. A set of results verifying the modelling technique, controller performance and effectiveness, displacements of cart, displacements and accelerations of the floors are presented and compared separately for passive and active modes in the form of graphics and tables.

Deflection Control of Two-Floors Structure Against Northridge Earthquake by Using PI Controlled Active Mass Damping

This paper presents an experimental investigation for deflection control of two degree of freedom building-like structure system against scaled Northridge Earthquake by using PI (Proportional-Integral) controlled active mass damping. Proposed structure consist of two floors with a cart mounted on the second floor such as active mass damping (AMD) and which is used to suppress horizontal deflections. Moreover a shake table under the structure is used to create the acceleration effect of scaled earthquake. Kp and Ki gain parameters of PI controller is determined by observing passive mode behaviour of the structure against Northridge and it is used to control cart movement according to pre-determined deflection criterias of the floors. Deflection and acceleration results of the floors are obtained separately for passive and active mode responses of the system in the form of graphics.

Optimisation of a PID Controller for an Inverted Pendulum Using the Bees Algorithm

The inverted pendulum system is a challenging control problem in the control theory, which continually moves away from a stable state. The paper presents the design of a Proportional-Integral-Derivative (PID) controller for a single-input multi-output (SIMO) inverted pendulum system and using the Bees Algorithm (BA) to obtain optimal gains for PID controllers. The Bees Algorithm optimizes the gains so that the controller can move the cart to a desired position with the minimum amount of the change in the pendulum’s angle from the vertically upright position during the movement. The tuning aim is to minimize the control responses of the cart’s position and the pendulum’s angle in time domain. MATLAB/Simulink simulation has been performed to demonstrate that the effects on the system performance of PID controllers with optimal gains. The obtained results show that the tuning method by using the Bees Algorithm produced PID controllers successfully within the controller design criteria. Following a description of the inverted pendulum system and the Bees Algorithm, the paper gives the obtained simulation results for the system demonstrating the efficiency of the design.