Adaptive depth control algorithm for sound tracing

2018 ◽  
Vol 24 (5) ◽  
pp. 21-30
Author(s):  
Eun Jae Kim ◽  
Woonam Chung ◽  
Woochan Park ◽  
Yun Juwon ◽  
Youngsik Kim
Keyword(s):  
Control Algorithm ◽  
Depth Control

Depth Control Method of AFM-Based Nanomachining with Diamond Tip in Deflection Mode

2007 ◽  
Vol 10-12 ◽  
pp. 578-582 ◽  
Author(s):  
Zhen Jiang Hu ◽  
Yong Da Yan ◽  
Tao Sun ◽  
Shen Dong ◽  
Z.Z. Zhao
Keyword(s):  
Theoretical Analysis ◽  
Penetration Depth ◽  
Theoretical Basis ◽  
Control Algorithm ◽  
Control Method ◽  
Normal Load ◽  
Penetration Process ◽  
Depth Control ◽  
Machining System

The equations correlated the normal load and the tip penetration depth were derived through the theoretical analysis of the penetration process of the diamond tip. Verified by experiments, the equations can reflect the penetration process of the scratching machining system and provide theoretical basis for the optimization of depth control algorithm. The control of scratching depth realized in AFM deflection mode can effectively restrain the system drift during scratching process.

ENHANCING THE YIELD OF HIGH-DENSITY ELECTRODE ARRAYS THROUGH AUTOMATED ELECTRODE SELECTION

2012 ◽  
Vol 22 (01) ◽  
pp. 1-19 ◽  
Author(s):  
GERT VAN DIJCK ◽  
KARSTEN SEIDL ◽  
OLIVER PAUL ◽  
PATRICK RUTHER ◽  
MARC M. VAN HULLE ◽  
...  
Keyword(s):  
Control Algorithm ◽  
Signal To Noise Ratio ◽  
Pyramidal Cells ◽  
Inhibitory Interneurons ◽  
Electrode Arrays ◽  
Signal To Noise ◽  
Detection Algorithms ◽  
Benchmark Data ◽  
Depth Control ◽  
Electrode Selection

Recently developed CMOS-based microprobes contain hundreds of electrodes on a single shaft with inter-electrode distances as small as 30 μm. So far, neuroscientists needed to select electrodes manually from hundreds of electrodes. Here we present an electronic depth control algorithm that allows to select electrodes automatically, hereby allowing to reduce the amount of data and locating those electrodes that are close to neurons. The electrodes are selected according to a new penalized signal-to-noise ratio (PSNR) criterion that demotes electrodes from becoming selected if their signals are redundant with previously selected electrodes. It is shown that, using the PSNR, interneurons generating smaller spikes are also selected. We developed a model that aims to evaluate algorithms for electronic depth control, but also generates benchmark data for testing spike sorting and spike detection algorithms. The model comprises a realistic tufted pyramidal cell, non-tufted pyramidal cells and inhibitory interneurons. All neurons are synaptically activated by hundreds of fibers. This arrangement allows the algorithms to be tested in more realistic conditions, including backgrounds of synaptic potentials, varying spike rates with bursting and spike amplitude attenuation.

scholarly journals Coordinated Depth Control of Multiple Autonomous Underwater Vehicles by Using Theory of Adaptive Sliding Mode

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Yintao Wang ◽  
Yani Zhang
Keyword(s):  
Control Algorithm ◽  
Sliding Mode ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Loop Control ◽  
Depth Control ◽  
The Common ◽  
Extended Graph ◽  
Rudder Angle ◽  
Theoretical Results

This paper addresses the coordinated depth control problem of multiple autonomous underwater vehicles, which means to maneuver a group of underwater vehicles which move at the same depth synchronously. Firstly, a coordinated error of depth between vehicles and the common desired depth is defined by using extended graph theory in a distributed manner; then a deep-pitch double loop control algorithm based on sliding mode is designed for each vehicle, by which each vehicle is driven to and move at the common depth coordinately. In particular, a pitch reference command is firstly calculated by the predefined coordinated depth error, which can be regarded as the outer loop control, and then, the input rudder angle for each vehicle is derived according to the pitch reference command being as the inner loop control. Considering the uncertainties of the model hydrodynamic parameters, an online parameter adaptive algorithm is introduced to improve the performance of the sliding mode control algorithm proposed. Simulations were performed to verify the theoretical results proposed.

scholarly journals PID Control Algorithm Based on Hydraulic Oil Viscosity for the Proportional Valve of the Planting Depth Control System

2020 ◽  
Author(s):  
Md. Abu Ayub Siddique ◽  
Wan-Soo Kim ◽  
Yeon-Soo Kim ◽  
Taek-Jin Kim ◽  
Chang-Hyun Choi ◽  
...  
Keyword(s):  
Control System ◽  
Pid Control ◽  
Control Algorithm ◽  
Power Flow ◽  
Maximum Pressure ◽  
Oil Viscosity ◽  
Temperature Dependent Viscosity ◽  
Proportional Valve ◽  
Planting Depth ◽  
Depth Control

This study was conducted to develop a PID control algorithm considering viscosity for the planting depth control system of a rice transplanter using various hydraulic oils at different temperatures and to evaluate the performance of the control algorithm, and compare the performance of the PID control algorithm without considering viscosity and considering viscosity. In this study, the simulation model of the planting depth control system and a PID control algorithm were developed based on the power flow of the rice transplanter (ERP60DS). The primary PID coefficients were determined using the Ziegler–Nichols (Z–N) second method. Routh’s stability criteria were applied to optimize the coefficients. The pole and double zero points of the PID controller were also applied to minimize the sustained oscillations of the responses. The performance of the PID control algorithm was evaluated for three ISO (The International Organization for Standardization) standard viscosity grade (VG) hydraulic oils (VG 32, 46, and 68). The results show that the control algorithm considering viscosity is able to control the pressure of the proportional valve, which is associated with the actuator displacement for various types of hydraulic oils. It was noticed that the maximum pressure was 15.405 bars at 0, 20, 40, 60, 80, and 100 ℃ for all of the hydraulic oils. The settling time and steady-state errors were 0.45 s at 100 ℃ for VG 32, and 0% for all of the conditions. The maximum overshoots were found to be 17.50% at 100 ℃ for VG 32. On the other hand, the PID control algorithm without considering viscosity could not control the planting depth, because the response was slow and did not satisfy the boundary conditions. The PID control algorithm considering viscosity could sufficiently compensate for the nonlinearity of the hydraulic system and was able to perform for any of temperature-dependent viscosity of the hydraulic oils. In addition, the rice transplanter requires a faster response for accurately controlling and maintaining the planting depth. Planting depth is highly associated with actuator displacement. Finally, this control algorithm considering viscosity could be helpful in minimizing the tilting of the seedlings planted using the rice transplanter. Ultimately, it would improve the transplanter performance.

scholarly journals Effects of Temperatures and Viscosity of the Hydraulic Oils on the Proportional Valve for a Rice Transplanter Based on PID Control Algorithm

Agriculture ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 73 ◽  
Author(s):  
Md. Abu Ayub Siddique ◽  
Wan-Soo Kim ◽  
Yeon-Soo Kim ◽  
Taek-Jin Kim ◽  
Chang-Hyun Choi ◽  
...  
Keyword(s):  
Control System ◽  
Pid Control ◽  
Control Algorithm ◽  
Power Flow ◽  
Maximum Pressure ◽  
Temperature Dependent Viscosity ◽  
Proportional Valve ◽  
Planting Depth ◽  
Response Characteristics ◽  
Depth Control

This study was conducted to develop a proportional-integral-derivative (PID) control algorithm considering viscosity for the planting depth control system of a rice transplanter using various hydraulic oils at different temperatures and to evaluate the performance of the control algorithm, and compare the performance of the PID control algorithm without considering viscosity and considering viscosity. In this study, the simulation model of the planting depth control system and a PID control algorithm were developed based on the power flow of the rice transplanter (ERP60DS). The primary PID coefficients were determined using the Ziegler-Nichols (Z-N) second method. Routh’s stability criteria were applied to optimize the coefficients. The pole and double zero points of the PID controller were also applied to minimize the sustained oscillations of the responses. The performance of the PID control algorithm was evaluated for three ISO (The International Organization for Standardization) standard viscosity grade (VG) hydraulic oils (VG 32, 46, and 68). The response characteristics were analyzed using statistical method (ANOVA) and Duncan’s multiple range test (DMRT) at a significant level of 0.05 were performed through the statistical software SPSS. The results show that the control algorithm considering viscosity is able to control the pressure of the proportional valve, which is associated with the actuator displacement for various types of hydraulic oils. It was noticed that the maximum pressure was 15.405 bars at 0, 20, 40, 60, 80, and 100 °C for all of the hydraulic oils. The settling time and steady-state errors were 0.45 s at 100 °C for VG 32 and 0% for all of the conditions. The maximum overshoots were found to be 17.50% at 100 °C for VG 32. On the other hand, the PID control algorithm without considering viscosity could not control the planting depth, because the response was slow and did not satisfy the boundary conditions. The PID control algorithm considering viscosity could sufficiently compensate for the nonlinearity of the hydraulic system and was able to perform for any of temperature-dependent viscosity of the hydraulic oils. In addition, the rice transplanter requires a faster response for accurately controlling and maintaining the planting depth. Planting depth is highly associated with actuator displacement. Finally, this control algorithm considering viscosity could be helpful in minimizing the tilting of the seedlings planted using the rice transplanter. Ultimately, it would improve the transplanter performance.

scholarly journals Model-Based Design (MBD) for Autonomous Underwater Vehicle

2019 ◽  
Vol 8 (12S2) ◽  
pp. 743-746
Keyword(s):  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Open Loop ◽  
Integrated Sensor ◽  
Pressure Sensing ◽  
Depth Data ◽  
Depth Control ◽  
The Comparative Study

This project is to enhanced and upgraded a depth controller for Autonomous Underwater Vehicle (AUV) to submerge precisely at the certain depth. This poster demonstrated an AUV equipped with integrated sensor and depth controller based on the pressure sensing which able to continuously sending the depth data to controller. The depth Simulink Arduino algorithm is implemented on an Arduino Mega using ModelBased Design (MBD) with MATLAB and Simulink. MBD used to model, simulate and verify the Simulink control algorithm after obtained data through open-loop experiment test. Then, it deploys and tests the algorithm on the embedded AUV hardware. The focus was in controlling the AUV vertical trajectory as the AUV tried to remain stationary at the selected depth and consuming its rise time Tr , overshoot Os , and settling time Ts are minimized. The comparative study for the AUV depth-control by On-Off, Proportional Integral Derivative (PID) controller and Fuzzy Logic Controller (FLC) controllers. MBD has faster implementation with fewer coding error when deploy to AUV hardware.

Automation of Process Control in Chemical Plant

2015 ◽  
Vol 2 (1) ◽  
pp. 6-12
Author(s):  
Agus Sugiarta ◽  
Houtman P. Siregar ◽  
Dedy Loebis
Keyword(s):  
Process Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Chemical Engineering ◽  
Chemical Plant ◽  
Raw Material ◽  
Flow Rates ◽  
Material Supply ◽  
Wide Range ◽  
Inherent Problem

Automation of process control in chemical plant is an inspiring application field of mechatronicengineering. In order to understand the complexity of the automation and its application requireknowledges of chemical engineering, mechatronic and other numerous interconnected studies.The background of this paper is an inherent problem of overheating due to lack of level controlsystem. The objective of this research is to control the dynamic process of desired level more tightlywhich is able to stabilize raw material supply into the chemical plant system.The chemical plant is operated within a wide range of feed compositions and flow rates whichmake the process control become difficult. This research uses modelling for efficiency reason andanalyzes the model by PID control algorithm along with its simulations by using Matlab.

Sign in / Sign up

Export Citation Format

Share Document