-Fixed-wing UAV has the ability to fly like a plane. For the movement of the flight, a good control system is needed. Part of the flight controls that require our attention among them is the vertical moving control. The controls are used to adjust the vertical movement involving aircraft pitch angle control. To control it, we can use control method that has been commonly used. The control method is a PID (Propositional, Integral and Derivative) control method. PID has three components (Kp, Ki, and Kd). The three components of PID can be obtained in various ways or methods. However, to produce a robust control, a method that can optimize the PID components is needed. Ant Colony Optimization (ACO) is one of PID controller optimization method which adapted by ant colony ability to find the shortest way from their nest to food. Some ACO parameters are a number of ants, parameters, and pheromone component for pheromone. Pheromones are the values given by the ants when they use the road.
Instant messaging services usually integrate a notification system on their users’ devices, as phone calls and short message service (SMS) systems do. Telegram is – as far as we are aware – the only popular instant messaging service that uses open source code. Telegram also provides APIs for their users, enabling the development of a bot system that allows instant messaging application to access information. Here, we study the potential use of Telegram bot as a user interface to a paperless office (PLO) system developed in our institution. We found that Telegram bot improves communication among the users; however, as the amount of messages increased, the server becomes overloaded. This limitation suggests that future works need to be directed to improving the efficiency of the bot
Personal recognition with image processing techniques from the side view has the disadvantage of being applied to the cashierless store environment, namely inaccurate recognition or identification when personal collisions occur. To overcome this, the image capture method is used from the top-view. Personal recognition method through the top-view image using the Haar Cascade Classifier method. 1420 positive images and 2170 negative images are used to find features that are considered suitable for recognizing objects using the Adaptive Boosting (Adaboost) method. Tests were carried out on 100 test data by varying the parameters of min_neighbors (3.4, and 5) and the size of the dataset window (25x25, 35x35, 45x45 pixels). Personal recognition testing gets the highest accuracy of 89.9% with the parameters used are min_neighbors 5 and the size of the 25x25 pixel dataset in the detection parameter size of min_size 140x140 pixels.
Landslides are one of the natural disasters that often occur in Indonesia. Therefore, this disaster cannot be eliminated, but it can minimize the disadvantage caused by an early warning mechanism. Early warning systems rely on a sensor node used to read soil conditions with specific parameters. Those parameters that are read lead to the detection of mass movements. With the tightness of the monitoring process, of course, a reliable sensor node is needed. However, there are challenges in how to minimize losses that occur due to damage to sensor nodes when landslides occur. Sensor nodes are made using IMU sensors to monitor mass movements and its use two processors, namely microcontroller and mini SBC, which are inexpensive to manufacture and do not require large space in the installation.
The ability of the quadrotor in the waypoint trajectory tracking becomes an essential requirement in the completion of various missions nowadays. However, the magnitude of steady-state errors and multiple overshoots due to environmental disturbances leads to motion instability. These conditions make the quadrotor experience a shift and even change direction from the reference path. As a result, to minimize steady-state error and multiple overshoots, this study employs a Linear Quadratic Regulator control method with the addition of an Integrator. Comparisons between LQR without Integrator and LQR with Integrator were performed. They were implemented on a quadrotor controller to track square and zig-zag waypoint patterns. From experimental results, LQR without Integrator produce of 2 meters steady-state error and -1.04 meters undershoot average with an accuracy of 64.84 % for square pattern, along 3.19 meters steady-state error, and -1.12 meters undershoot average with an accuracy of 46.73 % for a zig-zag way. The LQR method with integrator produce of 1.06 meters steady-state error with accuracy 94.96 % without multiple-overshoot for square pattern, the 1.06 meters steady-state error, and -0.18 meters undershoot average with an accuracy of 86.49 % for the zig-zag way. The results show that the LQR control method with Integrator can minimize and improve steady-state error and multiple overshoots in quadrotor flight. The condition makes the quadrotor able to flying path waypoints with the correct system specification. ABSTRAK: Kemampuan quadrotor dalam pengesanan lintasan waypoint menjadi syarat penting dalam menyelesaikan pelbagai misi pada masa kini. Walau bagaimanapun, besarnya ralat keadaan mantap dan banyak kelebihan kerana gangguan persekitaran menyebabkan ketidakstabilan pergerakan. Keadaan ini menjadikan quadrotor mengalami pergeseran dan bahkan mengubah arah dari jalur rujukan. Oleh itu, kajian ini menggunakan kaedah kawalan Linear Quadratic Regulator dengan penambahan integrator dalam meminimumkan ralat keadaan mantap dan banyak kelebihan. Perbandingan antara LQR tanpa Integrator dan LQR dengan Integrator dilakukan. Mereka dilaksanakan pada pengawal quadrotor untuk mengesan corak titik jalan persegi dan zig-zag. Dari hasil eksperimen, LQR tanpa Integrator menghasilkan ralat keadaan mantap 2 meter dan -1.04 meter rata-rata undur tembak dengan ketepatan 64.84% untuk corak persegi, sepanjang ralat keadaan tetap 3.19 meter, dan -1.12 meter rata-rata undur bawah dengan ketepatan 46.73 % untuk cara zig-zag. Kaedah LQR dengan integrator menghasilkan ralat keadaan mantap 1.06 meter dengan ketepatan 94.96% tanpa tembakan berlebihan untuk corak segi empat sama, ralat keadaan mantap 1.06 meter, dan rata-rata undur tembak -0.18 meter dengan ketepatan 86.49% untuk zig-zag cara. Hasilnya menunjukkan bahawa kaedah kawalan LQR dengan Integrator dapat meminimumkan dan memperbaiki ralat keadaan mantap dan banyak overhoot dalam penerbangan quadrotor. Keadaan tersebut menjadikan quadrotor dapat terbang ke titik jalan dengan spesifikasi sistem yang betul.
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