scholarly journals PERANCANGAN AUTOPILOT LATERAL-DIREKSIONAL PESAWAT NIRAWAK LSU-05 (THE DESIGN OF THE LATERAL-DIRECTIONAL AUTOPILOT FOR THE LSU-05 UNMANNED AERIAL VEHICLE)

2018 ◽  
Vol 15 (2) ◽  
pp. 93 ◽  
Author(s):  
Muhammad Fajar ◽  
Ony Arifianto
Keyword(s):  
State Space ◽  
Linear Model ◽  
Unmanned Aerial Vehicle ◽  
Pid Controller ◽  
Settling Time ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Directional Motion ◽  
Aerial Vehicle ◽  
Simulation Results

The autopilot on the aircraft is developed based on the mode of motion of the aircraft i.e. longitudinal and lateral-directional motion. In this paper, an autopilot is designed in lateral-directional mode for LSU-05 aircraft. The autopilot is designed at a range of aircraft operating speeds of 15 m/s, 20 m/s, 25 m/s, and 30 m/s at 1000 m altitude. Designed autopilots are Roll Attitude Hold, Heading Hold and Waypoint Following. Autopilot is designed based on linear model in the form of state-space. The controller used is a Proportional-Integral-Derivative (PID) controller. Simulation results show the value of overshoot / undershoot does not exceed 5% and settling time is less than 30 second if given step command. Abstrak Autopilot pada pesawat dikembangkan berdasarkan pada modus gerak pesawat yaitu modus gerak longitudinal dan lateral-directional. Pada makalah ini, dirancang autopilot pada modus gerak lateral-directional untuk pesawat LSU-05. Autopilot dirancang pada range kecepatan operasi pesawat yaitu 15 m/dtk, 20 m/dtk, 25 m/dtk, dan 30 m/dtk dengan ketinggian 1000 m. Autopilot yang dirancang adalah Roll Attitude Hold, Heading Hold dan Waypoint Following. Autopilot dirancang berdasarkan model linier dalam bentuk state-space. Pengendali yang digunakan adalah pengendali Proportional-Integral-Derivative (PID). Hasil simulasi menunjukan nilai overshoot/undershoot tidak melebihi 5% dan settling time kurang dari 30 detik jika diberikan perintah step.

scholarly journals PERANCANGAN SISTEM KONTROL NAVIGASI BEARING PADA QUADCOPTER DENGAN METODE PID (PROPORTIONAL, INTEGRAL, DERIVATIVE) SELF TUNING PSO (PARTICLE SWARM OPTIMIZATION)

TRANSIENT ◽  
2017 ◽  
Vol 6 (3) ◽  
pp. 323
Author(s):  
Muhammad Surya Sulila ◽  
Sumardi Sumardi ◽  
Munawar Agus Riyadi
Keyword(s):  
Particle Swarm Optimization ◽  
Global Position System ◽  
Unmanned Aerial Vehicle ◽  
Particle Swarm ◽  
Settling Time ◽  
Proportional Integral Derivative ◽  
Swarm Optimization ◽  
Proportional Integral ◽  
Self Tuning ◽  
Aerial Vehicle

Unmanned Aerial Vehicle (UAV) adalah pesawat tanpa awak yang dapat dikendalikan secara manual ataupun otomatis dari jarak jauh. Sistem navigasi UAV quadcopter salah satunya adalah membuat sistem kontrol quadcopter agar dapat stabil menghadap ke arah koordinat yang dituju dengan mengatur sudut putar sumbu vertikal (yaw) atau disebut navigasi bearing sehingga pada Penelitian ini dirancang sistem kontrol Proportional Integral Derivative self tuning Particle Swarm Optimization. Perancangan sistem navigasi bearing digunakan input berupa Global Position System untuk mengetahui koordinat quadcopter, sedangkan sensor kompas HMC5883L digunakan untuk mengetahui kondisi aktual sudut arah hadap quadcopter. Berdasarkan hasil pengujian respon sistem quadcopter, untuk dapat mengarah ke koordinat yang dituju dengan koordinat quadcopter tetap, settling time dicapai pada detik ke 6,4 dan error setelah settling time sebesar 5,4⁰. Berdasarkan pengujian dengan perubahan koordinat, didapatkan error rata-rata sebesar 7,9⁰. Berdasarkan pengujian dengan diberi gangguan didapatkan error offset rata-rata sebesar 1,89⁰ dan mencapai settling time pada detik ke 4,1. Batasan nilai self tuning PSO yang terbaik didapat pada nilai Kp = 0,15 sampai 0,3, Ki = 0,06 sampai 0,6, dan Kd = 0,005 sampai Kd = 0,1. Nilai koefisien PSO yang digunakan adalah C1 = 1,5,  C2 = 2 dan bobot inersia dari 0,7 sampai 1,2.

scholarly journals Position Tracking of ML System using CSA Based PID Controller

2019 ◽  
Vol 8 (11) ◽  
pp. 1956-1959
Keyword(s):  
Pid Controller ◽  
Magnetic Levitation ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Pid Controllers ◽  
Position Tracking ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Simulation Results

The classical proportional integral derivative (PID) controllers are still use in various applications in industry. Magnetic levitation (ML) systems are rigidly nonlinear and sometimes unstable systems. Due to inbuilt nonlinearities of ML systems, tracking of position of ML Systems is still difficult. For the tracking purpose of position, PID controller parameters are found by choosing Cuckoo Search Algorithm (CSA) of optimization. The ranges of parameters are customized by z-n method of parameters. Simulation results show the tracking of position of ML systems using conventional and optimized parameters obtained with the CSA based controller.

Modelling and PID Control of a Quadrotor Aerial Robot

2014 ◽  
Vol 903 ◽  
pp. 327-331 ◽  
Author(s):  
Ismail Mohd Khairuddin ◽  
Anwar P.P.A. Majeed ◽  
Ann Lim ◽  
Jessnor Arif M. Jizat ◽  
Abdul Aziz Jaafar
Keyword(s):  
Pid Control ◽  
Pitch Angle ◽  
Pid Controller ◽  
Pd Controller ◽  
Proportional Integral Derivative ◽  
Hovering Flight ◽  
Proportional Integral ◽  
Aircraft Model ◽  
Aerial Robot ◽  
Aerial Vehicle

This paper elucidates the modeling of a + quadrotor configuration aerial vehicle and the design of its attitude and altitude controllers. The aircraft model consists of four fixed pitch angle propeller, each driven by an electric DC motor. The hovering flight of the quadrotor is governed by the Newton-Euler formulation. The attitude and altitude controls of the aircraft were regulated using heuristically tuned (Proportional-Integral-Derivative) PID controller. It was numerically simulated via Simulink that a PID controller was sufficient to bring the aircraft to the required altitude whereas the attitude of the vehicle is adequately controlled by a PD controller.

Dynamic Modeling for a Miniature Six-Rotor Unmanned Aerial Vehicle

2013 ◽  
Vol 321-324 ◽  
pp. 819-823 ◽  
Author(s):  
Qi Dong Ma ◽  
Zhen Guo Sun ◽  
Jing Ran Wu ◽  
Wen Zeng Zhang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Driving Force ◽  
Pid Controller ◽  
Control Algorithm ◽  
Driving Forces ◽  
Euler Angles ◽  
Unstable System ◽  
Nonlinear Dynamic Model ◽  
Aerial Vehicle ◽  
Simulation Results

A nonlinear dynamic model of a miniature Six-Rotor is presented. A 4 channels PID controller is designed to operate the under actuated and dynamically unstable system with 6 inputs. Driving forces of 6 rotors are divided into four components such as throttle, roll, pitch and yaw. The control algorithm is simulated with Design Optimization Toolbox in Matlab. After observing the corresponding responses of Euler angles, the altitude and the driving force for each motor, the simulation results show good performance.

scholarly journals Simulation of a Self-Balancing Platform on the Mobile Car

2021 ◽  
Vol 17 (3) ◽  
pp. 29-44
Author(s):  
Bushra Amer Tawfeeq ◽  
Maher Yahya Salloom ◽  
Ahmed Alkamachi
Keyword(s):  
Dynamic Model ◽  
Pid Controller ◽  
The Self ◽  
Simple Design ◽  
Proportional Integral Derivative ◽  
Simulated Model ◽  
Proportional Integral ◽  
Road Disturbance ◽  
Simulation Results ◽  
Biomedical Fields

        In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, industry. This paper introduced the simulated model of a proposed self-balancing platform that described the self–balancing attitude in (X-axis, Y-axis, or both axis) under the influence of road disturbance. To simulate the self-balanced platform's performance during the tilt, an integration between Solidworks, Simscape, and Simulink toolboxes in MATLAB was used. The platform's dynamic model was drawn in SolidWorks and exported as a STEP file used in the Simscape Multibody environment. The system is controlled using the proportional-integral-derivative (PID) controller to maintain the platform leveled and compensate for any road disturbances. Several road disturbances scenarios were designed in the x-axis, y-axis, or both axis (the pitch and roll angles) to examine the controller effectiveness. The simulation results indicate that that the platform completed self-balancing under the effect of disturbance (10° and -10°) on the X-axis, Y-axis, and both axes in less than two milliseconds. Therefore, a proposed self-balancing platform's simulated model has a high self-balancing accuracy and meets operational requirements despite its simple design.  

DVCC+ Based Immittance Function Simulators Including Grounded Passive Elements Only

2021 ◽  
pp. 2150278
Author(s):  
Tayfun Unuk ◽  
Erkan Yuce
Keyword(s):  
Pid Controller ◽  
Mixed Mode ◽  
Proportional Integral Derivative ◽  
Passive Element ◽  
Passive Components ◽  
Proportional Integral ◽  
Multifunction Filter ◽  
Minimum Number ◽  
Simulation Results ◽  
Matching Constraints

Eight new immittance function simulators (IFSs) with only grounded passive elements are proposed in this paper. All of the IFSs consist of only two DVCC+s and a minimum number of passive components without needing any passive element matching constraints. Each of the proposed IFSs can provide one of [Formula: see text]L with series [Formula: see text]R and [Formula: see text]L with parallel [Formula: see text]R. As an application example, a second-order mixed-mode (MM) multifunction filter is developed from the proposed +L with series +R and +L with parallel +R. Furthermore, a proportional integral derivative (PID) controller is derived from the proposed +L with series +R. Many simulation results through the SPICE program and several experimental ones are included to verify the theory.

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