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This study presents a position tracking control method, with reference to Data-Driven Predictive Controller (DDPC), for a Pneumatic Artificial Muscle (PAM) system. The design of predictive controller is created from the subspace identification matrices acquired by input/output data. The control scheme is entirely data-based without explicit use of a model in the control application that can rectify the nonlinearity and uncertainties of the PAM. Firstly, subspace matrices are developed employing the identification method as a predictor by using open-loop experiments. Secondly, the estimated subspace matrices are used to design the so-called DDPC. In this instance, the quadratic programming (QR) decomposition method is used to obtain the prediction matrices. Consequently, experiments are carried out by the PAM actuator with different testing and loading conditions. The real-time experimental results demonstrate the feasibility and efficiency of the suggested control approach for nonlinear systems. © 2012-2019 ICI Bucharest.

Applied computer laboratory lessons could be unproductive because of many students in there. Correcting students' mistakes one by one is wasting lesson time. Especially for beginners, most of these mistakes caused by complex integrated development environments. In this study, we develop a client server application for computer laboratories. Developed application is able to compile programming language source code remotely. Thus, students don't need to make something out of the writing source code. Furthermore, instructors don't need to install compiler to the each computer in laboratory. For start lesson, it is enough that server has just been configured. (C) 2015 The Authors. Published by Elsevier Ltd.

This paper presents the design of tendon-driven actuated fingers using a shape memory alloy for a hybrid anthropomorphic prosthetic hand. The ring and little (pinky) fingers are selected for shape memory activation due to their lower degree of movement during multiple grasping configurations. The fingers' tendon system is based on shape memory alloy (SMA) wires that form artificial muscle pairs for the required flexion/extension of the finger joints. The finger has four degrees of freedom such that three of them are active. An experimental setup was developed to evaluate the performance of the ring and little fingers. An electromyography (EMG) controlled Pulse Width Modulated (PWM) technique is preferred for the actuation of joint motions using a high speed microcontroller.