Penelitian ini membahas perancangan robot Arm Gripper yang berbasis Arduino Uno dengan menggunakan LabView sebagai antarmuka (interface). Arduino Uno digunakan untuk mengendalikan motor servo yang merupakan aktuator. Sedangkan software Labview dimanfaatkan sebagai antarmuka untuk memantau sistem secara real time. Pengoperasian dan pengamatan robot ini sepenuhnya pada tampilan yang telah dibuat pada LabView.
Building energy monitoring systems are carried out to facilitate the monitoring and controlling of building energy consumption. Monitoring and controlling the use of electrical energy in real-time in a building has an impact on the pattern of regulating the efficiency level of energy use. This paper presents an effort to optimize energy consumption by using an energy management system using LoRa modulation and MQTT protocols. Sensors that feed electrical power data to a custom energy monitoring system are compiled by a set of sensors equipped with a power supply that is fastened to the system on a microcontroller with a LoRa communication interface then are called nodes. The nodes consist of arduino uno as a microcontroller, dragino LoRa Shield, ACS712 current sensor, ZMPT101B voltage sensor, and relay. Dragino LoRa Gateway LG01-N is used to connect the measured parameters to the IoT cloud server. MQTT protocol is used for the broker between nodes and servers using subscribe and publish method. In the initial experiments, the data visualization platform used was the open-source thingspeak platform. This platform includes a data visualization template and enables device control for savings. In the end nodes, the voltage, current, and power sensor accuracy error are 1,24%, 2.60%, and 3.13%.
The electric motor is one of the technological developments which can support the production process. DC motor has some advantages compared to AC motor especially on the easier way to control its speed or position as well as its widely adjustable range. The main issue in the DC motor is controlling the angular speed with uncertainty and disturbance. The alternative solution of a control method with simple, easy to design, and implementable in a multi-input multi-output system is integral state feedback such as linear quadratic Gaussian (LQG). It is a combination between linear quadratic regulator and Kalman filter. One of the advantages of this method is the usage of fewer sensors compared with the original linear quadratic regulator method which uses sensors as many as the state in the system model. The design, simulation, and experimental study of the application of LQG as state feedback control in a DC-drive system have been done. Both performance and energy were analyzed and compared with conventional proportional integral derivative (PID). The gain of LQG was determined by trial whereas the PID gain is determined from MATLAB autotuning without fine-tuning. The load test and tracking test were carried out in the experiment. Both simulation and hardware tests showed the same result which LQG is superior in integral absolute error (IAE) by up to 74.37 % in loading test compared to PID. On the other side, LQG needs more energy, it consumes higher energy by 6.34 % in the load test.
The electric motor is an electromagnetic device that converts electrical energy into mechanical energy. There are many industrial sectors using electrical motors. Almost 90% of industries still use PID control because of its simplicity, applicability, and reliability. However, the weakness of PID is that it takes a long time to tune. PSO is one of the optimization methods which can be used to tune PID. The objective function is needed when using PSO to tune PID control. Five different objective functions which are ISE, IAE, ITSE, ITAE, and MSE is compared in terms of performance and control energy. The PID controller is applied in DC motor speed control in a simulation environment. Three testing condition is carried out which is step responses, set-point changes, and disturbance rejection. The simulation result shows that in terms of performance, ITSE is the best one. On the other hand, in terms of control energy, ISE is using the lowest energy to control the plant.
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