Hendro Nurhadi

Ensemble and Fuzzy Kalman Filter for position estimation of an autonomous underwater vehicle based on dynamical system of AUV motion

Ensemble Kalman Filter (EnKF) algorithm can be applied to estimate AUV position.Fuzzy Kalman Filter (FKF) algorithm can be applied to estimate AUV position.The system dynamic of AUV motion is used for true trajectory of estimation.EnKF estimation is better than FKF estimation in AUV position estimation.Performance of each method based on RMSE and computational time. An underwater vehicle is useful in the monitoring of the unstructured and dangerous underwater conditions. One of the unmanned underwater vehicle is AUV. AUV is a robotic device that is driven through the water by a propulsion system, controlled and piloted by an onboard computer, and maneuverable in three dimensions. This research explains about position estimation of AUV based on the Ensemble Kalman Filter (EnKF) and the Fuzzy Kalman Filter (FKF). EnKF is used as the estimation method of AUVs position that maneuvering in 6 DOF (Degrees of Freedom) with the specified trajectory. The estimation results are simulated with Matlab. The simulations show the AUV position estimation based on the EnKF with some of the different ensembles and the comparison results of the position estimation between the EnKF and the FKF. The final result of these study shows that Ensemble Kalman Filter is better to estimate the trajectory of the dynamical equation of AUV motion with the error estimation of EnKF is 92% smaller in the x-position dan y-position, 6.5% smaller in the z-position, 93% smaller in the angle dan the computation of time is 50% faster than the estimation results of FKF.

Control simulation of an Automatic Turret Gun based on force control method

Automatic Turret Gun (ATG) is a weapon system used in numerous combat platforms and vehicles such as in tanks, aircrafts, or stationary ground platforms. ATG plays a big role in both defensive and offensive scenario. It allows combat engagement while the operator of ATG (soldier) covers himself inside a protected control station. On the other hand, ATGs have significant mass and dimension, therefore susceptible to inertial disturbances that need to be compensated to enable the ATG to reach the targeted position quickly and accurately while undergoing disturbances from weapon fire or platform movement. The paper discusses various conventional control method applied in ATG, namely PID controller, RAC, and RACAFC. A number of experiments have been carried out for various range of angle both in azimuth and elevation axis of turret gun. The results show that for an ATG system working under disturbance, RACAFC exhibits greater performance than both RAC and PID, but in experiments without load, equally satisfactory results are obtained from RAC. The exception is for the PID controller, which cannot reach the entire angle given.

Multistage Rule-Based Positioning Optimization for High-Precision LPAT

This paper proposes a multistage rule-based precision positioning control method for the linear piezoelectrically actuated table (LPAT). During the coarse-tuning stage, the LPAT is actuated by coarse voltage schemes toward the target of 20 μm at a higher velocity, and during the fine-tuning stage, it is steadily and accurately driven by the fine voltage scheme to reach the target position. The rule-based method is employed to establish the control rules for the voltages and displacements of the two stages using statistical methods. The experimental results demonstrate that the proposed control method can quickly reach steady state, and the steady-state error can be reduced to less than or equal to 0.02 μm for small travel (±0.1 μm) and large travel (± 20 mm).

Estimate and control position autonomous Underwater Vehicle based on determined trajectory using Fuzzy Kalman Filter method

Unmanned Underwater Vehicle (UUV), known as underwater drones, are any vehicle that are able to operate underwater without human occupant. AUV (Autonomous Underwater Vehicle) are one of categories of these vehicles which operate independently of direct human input. This AUV is required to have a navigation system that can manoeuvred 6 Degree of Freedom (DOF) and able to estimate the exact position based on the determined trajectory. Fuzzy Kalman Filter (FKF) method is used to estimate the position of the AUV. This process is used to maintain the accuracy of the trajectory. The performance of FKF algorithm on some several trajectory cases show that this method has relatively small Root Means Square Error (RSME), which is less than 10%.

Navigation and guidance control system of AUV with trajectory estimation of linear modelling

This paper put forwards a study on the development of navigation and guidance systems for AUV. The restriction in AUV model and estimation on the degree of freedom are recognized as the common problem in AUVs navigation and guidance systems. In this respect a linear model, derived from the linearization using the Jacobian matrix, will be utilized. The so obtained linear model is then estimated by the Ensemble Kalman Filter (EnKF). The implementation of EnKF algorithm on the linear model is carried out by establishing two simulations, namely by generating 300 and 400 ensembles, respectively. The simulations exhibit that the generation of 400 ensembles will give more accurate results in comparison to the generation of 300 ensembles. Furthermore, the best simulation yields the tracking accuracy between the real and simulated trajectories, in translational modes, is in the order of 99.88%, and in rotational modes is in the order of 99.99%.

Design of Autonomous Underwater Vehicle motion control using Sliding Mode Control method

This paper presents a study of the Autonomous Underwater Vehicle (AUV). Nonlinear model of AUV which has six degrees of freedom being linearized using Jacobian matrix. In this paper, Sliding Mode Control law as a method is applied Autonomous Underwater Vehicle and the simulation obtained a stable performance.

Study on controller designs for high-precisely linear piezoelectric ceramic motor (LPCM)

The aim of this paper is an observation of PID, fuzzy, sliding mode (SM) and fuzzy-sliding mode (FSM) controllers for high-precisely linear piezoelectric ceramic motor (LPCM). By understanding the characteristics of each single controller, one of the advantages is well-knowledge, when those controllers will be used, and what drawbacks they have. This paper exhibit a comparison of their error-reduction performance. It shows that the FSM is the most robust adaptive controller than others such as PID, fuzzy logic system or sliding mode.

Inverse Kinematics Modelling and Simulation for Upper Case Writing Robot Control Using ANFIS

Robotics has lots of use in the industrial world and has lots of development since the industrial revolution, due to its qualities of high precision and accuracy. This paper is designed to display the qualities in a form of a writing robot. The aim of this study is to construct the system based on data gathered and to develop the control system based on the model. There are four aspects studied for this project, namely image processing, character recognition, image properties extraction and inverse kinematics. This paper served as discussion in modelling the robotic arm used for writing robot and generating theta for end effector position. Training data are generated through meshgrid, which is the fed through anfis.

Preliminary Study on Magnetic Levitation Modeling Using PID Control

This paper proposes to understand about basic magnetic levitation model. Magnetic Levitation is repulsive or attractive force resulting gap from magnetic field. Characteristic of the magnetic levitation model is used permanent magnet and electromagnet with PID control to maintain wide gap between levitator and object levitation. Mass addition is used to analysis the model of the Maglev with PID control to maintain wide gap. Calculation result show that the maglev with PID control has sufficient levitation force in the maintain wide gap. Comparison between calculated and measured values can be done to build a another complex model magnetic levitation.

Preliminary Numerical Study on Designing Navigation and Stability Control Systems for ITS AUV

In this paper, the numerical study of designing on navigation and stability control system for AUV is studied. The study started by initiating hydrostatic forces, added masses, lift force, drag forces and thrust forces. Determining the hydrodynamic force which is the basic need to know the numerical case study on designing on navigation and stability control system for AUV where Autonomous Underwater vehicles (AUV). AUV is capably underwater vehicle in moving automatically without direct control by humans according to the trajectory. The result of numerical study is properly to be the reference for the next developing for AUV.