Abstract: This work presents a simulation of a realistic way to guide the non-redundant 6-DOF Quadrotor Manipulation System (QMS) toward the target object, in preparation for catching it. Depending only on the teleoperation process to drive a QMS to do this task is a very difficult and slow process because of a human capability. In this paper, two stages are presented. Firstly, guiding the teleoperation process of the QMS by controlling its position and orientation until the target object becomes in the camera Field Of View (FOV). Secondly, a vision system is used to autonomously guide the QMS toward the object until it becomes accessible to the robot gripper. This will significantly increase both the speed and accuracy of the whole process. For these two steps, Position Holding Scheme (PHS) and Image-Based Visual Servoing (IBVS) are used. The proposed QMS is a non-redundant 6-DOF robot, which is characterized by a minimum number of actuators, low power consumption, non-complex controller compared to a redundant QMS. It consists of a 2-serial link robotic arm installed at the quadrotor's Center Of Mass (COM) with a unique topology, that provides maximum mobility with minimum possible weight. In other words, there are 6 actuators only to perform the required 6-DOF. A camera/vision sensor is attached to the end-effector to form eye-in-hand architecture. The system kinematics and dynamics are illustrated. A fifth-order quintic polynomial is utilized with Image-Based Visual Servoing (IBVS) to smoothly guide the system toward the target object and to avoid losing it. The PID controller is used to control the 6-DOF simultaneously during autonomous mode. Besides, it is used to control the teleoperation process. The proposed system is designed and tested using MATLAB/ADAMS co-simulation programs. The simulation results indicate that this system can perform dual tasks, manual and autonomous guiding.

Abstract: Mobile robots in industrial applications can profit from the utilize of wireless communication systems. However, the nature of the networked control system induces the time delay which can lead to instability of the control loop or even degradation of the control performance. This paper illustrates a quadratic curve path tracking based Smith adaptive approach and its application to control a two-wheeled mobile robot whose close-loop consists of the mobile robot connected through a wireless network to the controller. First, a kinematic based controller using the quadratic curve is adopted for tracking the desired path. Second, the future state of the mobile robot’s control system is estimated by the Smith predictor approach to mitigate the negative effect of the network time delay. Then, a model reference adaptive controller using the future state is built to deal with parametric uncertainties in the mobile robot control system with delays. Some simulation studies carried out to evaluate the effectiveness and performance of the proposed controller illustrate that the proposed controller is a more efficient and effective operation for path tracking control in the presence of time delay.

Abstract: The potential use of solar electricity in Indonesia is very large, the geographical position and climatic conditions that exist in the equatorial zone, where the intensity of solar radiation can run on average for (10-12) hours / day [1]. The production of electricity produced by solar panels over time is generally relatively fluctuating. To anticipate the state of these fluctuations, a DC-DC buck converter is needed. In addition, a control system is needed to regulate electrical power products to meet standards. DC-DC buck converter is a device that serves to decrease or increase the voltage level of a PV product, then the voltage value is maintained at a certain level. This study aims at how PV is able to produce electrical power products that are determined through fuzzy logic control power can then be stored in a battery charging system, by implementing battery switching mode from a power source that comes from solar panels. The set point for output voltage DC-DC power converter buck is set at the voltage level = 15.60 Volts. The presence is monitored through a CPS (Cyber Physics System) based system. In Fuzzy Logic Control (FLC) the system output is a pulse width modulation (PWM) signal generator associated with the duty-cycle value. At the simulation stage compared to the real system, the system has an average deviation = 0.074%. From testing the system with FLC, where the set point is worth 15.82 volts, then the system performance is: For data sampling = 1 minute able to produce a maximum voltage = 15.82 volts, maximum overshoot = 1.15%, peak time = 46 minutes, rise time = 11 minutes, settling time for steady state error criteria (ess 2%) = 55 minutes. As for the FLC set point with a minimum voltage = 15.35 volts, the switching performance for charging if the battery has reached 100% charging, the relay will disconnect the charging system switch. The effective time required for a charging system with a 1.3 Ampere current input, requires a charging time of 3 hours. In a state of charging battery 1 and battery 2 have been filled up to 50% capacity, measurement of voltage, current and output power on the buck converter; is = (15,582 ± 0.0084) volts, = (1,170 ± 0.015) amperes = (18,230 ± 0.232) Watts.

Abstract: Heat transfer improvement in heat exchanger systems has important benefits in the industrial sector. It helps reduce the losses, improve the overall efficiency of any industrial process. This paper presents both experimental & numerical studies to verify the improvement of heat transfer of heavy fuel oil HFO in the circular tube of the heat exchanger fitted with metal linkages (metal chains). The heavy fuel oil was passed through the test tube under turbulent flow conditions, and uniform heat flux on the external wall of 150°C with Reynolds number ranges from 5,000 to 15,000. Metal chains used in this study have P/D=1, 2, 3, 4 & 5, and t/D= 0.1 & 0.15, where P is ring length, D is the tube diameter, and t is the wire diameter. Both experimental and simulation results show that the metal-chain insertion increased the thermal performance factor (η) and Nusselt number of the heat exchanger. The friction factor (f) also increases with the presence of the metal chains in the tube. Thermal performance factor (η) also decreases with increasing Reynolds number for all cases. The highest thermal performance factor (η) was found with P/D= 3 & t/D= 0.15 while the highest Nu and f was found with P/D= 1 & t/D= 0.15. In addition to that, the numerical study showed that the use of metal chains inside the tubes of the heat exchanger would change the behavior of the flow and generate vortices, which heat transfer enhancement.

Abstract: An experimental investigation was conducted to explore the effect of different mesh size of kenaf core (KC) reinforced composite on impact energy absorption. The composite was fabricated by using soft epoxy (SE) and Polyurethane (PU) as a matrix and different size of KC as a reinforcement. The size of KC used was 3 mm, 20 mesh and 40 mesh. There were 27 layup sequence with two types of matrix (SE and PU) and cold press process was used. The impact testing was tested on all fabricated composites. From the results, it was found that the ACA layup sequence specimen reinforced PU has the highest energy absorption of 208.5 % higher compare to pure PU foam. It was also found that the ACC layup sequence reinforced SE can be absorbed energy of 9.90 J. Based on the results, it can be concluded that the smaller the mesh size of KC used, the better performance in impact energy absorption.

Abstract: This paper presents a robotic grasp-to-place system that has the capability of grasping objects in sparse and cluttered environments. The key feature of the system is that it handles both primitive actions of picking and placing of objects with an explicit framework using raw RGB-D images. Thus, the contribution of this paper is to model such a complete manipulation system with reasonable computational complexity. To achieve this, the camera captured RGB images of the scene, and 3d point cloud information are used to generate heightmaps at the robot grasp-workspace. The heightmap is rotated by 36 different angles before feeding into the network in order to generate a set of 36 pixel-wise Q-value maps, which is then passed into a Dense Network (DenseNet) to generate predictions of Q-values. Q-values are a measure of future expected reward in the formula of Q-learning from reinforcement learning. This effectively gives us values for predictions for 36 different grasping angles for every visible location in the robot grasp-workspace. In the simulation, exhaustive experimental results demonstrate that our framework successfully grasp objects with a grasp success rate and grasp efficiency, at almost 80~95% for both. As for place task, our framework successfully placed objects with a place success rate to at least 90 % through all test-cases.

Abstract: The current work describes biodiesel production intensification from waste cooking oil (WCO) utilizing a hydrodynamic cavitation reactor (HCR) via the transesterification reaction. The goals of this study were to focus on interactive effect and optimizing various process parameters. The response surface methodology (RSM) was performed for experimental design and analyzed the interactive effects of various process parameters. These variable process parameters were studied, including inlet pressure, methanol to oil molar ratio, catalyst concentration (potassium hydroxide, KOH), and reaction time. The results revealed that an inlet pressure, methanol to oil molar ratio, and catalyst concentration have the important biodiesel yield parameters. The optimal conditions for these parameters were determined as an inlet pressure of 3.95 bar, methanol to oil molar ratio of 5.86:1, 1.26 wt.% of KOH, and a reaction time 26.51 min. Under optimal conditions, the biodiesel yield's predicted and experimental values were 96.1% and 95.1%, respectively. According to the results, the predicted values were agreed with the experimental values. Thus, RSM is a reliable way of modeling the transesterification process.