scholarly journals An Internal Model-Based PID Control for Smart Shot Peening Operation

2021 ◽  
pp. 15-33
Author(s):  
V. B. Nguyen ◽  
T. Ba ◽  
A. Teo ◽  
K. Ahluwalia ◽  
A. Aramcharoen ◽  
...  
Keyword(s):  
Control System ◽  
Pid Control ◽  
Shot Peening ◽  
System Development ◽  
Pressure Sensors ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Model Based ◽  
Extreme Gradient Boosting ◽  
Site Control

Current control systems for the shot peening operation merely rely on old technologies, which often require repetitive processes to obtain pre-validated Almen systems to guide industrial productions. These designs for the manufacturing paradigm are not efficient for complicated workflows in modern manufacturing operation. Thus, in this study, we propose a practical model-based control system to address the issues; especially for a smarter and automated shot peening machine. In particular, the closed-loop control system development utilizes a model-based proportional-integral-derivative (PID) control technology and extreme gradient boosting (XGBOOST) machine learning algorithm. The control system includes an internal process model, a proxy model, a model-based PID controller, and pressure sensors with a low-pass filter for feedback control. The developed control system is integrated into a physical shot peening machine for on-site control validation and demonstration. In both in-silico and on-site control demonstrations, the obtained control performance is stable, robust, and reliable for different operational conditions. The measurement intensities are very close to targeted setting intensities. All the differences are smaller than the industrial threshold of (±0.01 mmA). It implies that the control system can use in industrial peening operations without the need for Almen system development for operational guidance. In other words, the control system can significantly reduce the total cost of the actual production by eliminating the cost, time, and labor of the iterative trials to build the Almen system.

scholarly journals Stabilization of the Magnetic Levitation System

2021 ◽  
Vol 11 (21) ◽  
pp. 10369
Author(s):  
Štefan Chamraz ◽  
Mikuláš Huba ◽  
Katarína Žáková
Keyword(s):  
Closed Loop ◽  
Magnetic Levitation ◽  
Internal Model Control ◽  
Pass Filter ◽  
Low Pass Filter ◽  
First Order ◽  
Model Based ◽  
Model Control ◽  
Levitation System ◽  
Magnetic Levitation System

This paper contributes toward research on the control of the magnetic levitation plant, representing a typical nonlinear unstable system that can be controlled by various methods. This paper shows two various approaches to the solution of the controller design based on different closed loop requirements. Starting from a known unstable linear plant model—the first method is based on the two-step procedure. In the first step, the transfer function of the controlled system is modified to get a stable non-oscillatory system. In the next step, the required first-order dynamic is defined and a model-based PI controller is proposed. The closed loop time constant of this first-order model-based approach can then be used as a tuning parameter. The second set of methods is based on a simplified ultra-local linear approximation of the plant dynamics by the double-integrator plus dead-time (DIPDT) model. Similar to the first method, one possible solution is to stabilize the system by a PD controller combined with a low-pass filter. To eliminate the offset, the stabilized system is supplemented by a simple static feedforward, or by a controller proposed by means of an internal model control (IMC). Another possible approach is to apply for the DIPDT model directly a stabilizing PID controller. The considered solutions are compared to the magnetic levitation system, controlled via the MATLAB/Simulink environment. It is shown that, all three controllers, with integral action, yield much slower dynamics than the stabilizing PD control, which gives one motivation to look for alternative ways of steady-state error compensation, guaranteeing faster setpoint step responses.

PMSM Control System Based on a Improved Sliding Mode Observer

2013 ◽  
Vol 307 ◽  
pp. 27-30 ◽  
Author(s):  
Yu Feng Zhang ◽  
Sheng Jin Li ◽  
Yong Zhou ◽  
Qi Xun Zhou
Keyword(s):  
Control System ◽  
Vector Control ◽  
Sliding Mode ◽  
Interpolation Method ◽  
Linear Interpolation ◽  
Sliding Mode Observer ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Field Oriented Vector Control ◽  
Vector Control System

In order to improve the performance of sensorless PMSM control system, an improved sliding mode observer (SMO) is proposed in this paper. To decrease the vibration of SMO, a variable switching gain which changes according to the winding currentn is adopted. To improve the estimated value of rotor position, a extra low pass filter (LPF) is employed and the linear interpolation method is used to calculate compensation value of the phase delay caused by LPF. To verify the performance of proposed SMO, a sensorless field oriented vector control system of PMSM is designed. At last, the performance of the improved SMO and the sensorless PMSM vector control system are verified by experimental results.

scholarly journals Design consideration in low dropout voltage regulator for batteryless power management unit

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Mohamad Khairul bin Mohd Kamel ◽  
Yan Chiew Wong
Keyword(s):  
System Development ◽  
Maximum Load ◽  
Open Loop ◽  
Low Noise ◽  
Green Technology ◽  
Voltage Regulator ◽  
Cmos Process ◽  
Process Technology ◽  
Pass Filter ◽  
Low Pass Filter

Harvesting energy from ambient Radio Frequency (RF) source is a great deal toward batteryless Internet of Thing (IoT) System on Chip (SoC) application as green technology has become a future interest. However, the harvested energy is unregulated thus it is highly susceptible to noise and cannot be used efficiently. Therefore, a dedicated low noise and high Power Supply Ripple Rejection (PSRR) of Low Dropout (LDO) voltage regulator are needed in the later stages of system development to supply the desired load voltage. Detailed analysis of the noise and PSRR of an LDO is not sufficient. This work presents a design of LDO to generate a regulated output voltage of 1.8V from 3.3V input supply targeted for 120mA load application. The performance of LDO is evaluated and analyzed. The PSRR and noise in LDO have been investigated by applying a low-pass filter. The proposed design achieves the design specification through the simulation results by obtaining 90.85dB of open-loop gain, 76.39º of phase margin and 63.46dB of PSRR respectively. The post-layout simulation shows degradation of gain and maximum load current due to parasitic issue. The measurement of maximum load regulation is dropped to 96mA compared 140mA from post-layout. The proposed LDO is designed using 180nm Silterra CMOS process technology.

scholarly journals Sloshing Simulation of Single-Phase and Two-Phase SPH using DualSPHysics

Kapal ◽  
2020 ◽  
Vol 17 (2) ◽  
pp. 50-57
Author(s):  
Andi Trimulyono ◽  
S Samuel ◽  
Muhammad Iqbal
Keyword(s):  
Free Surface ◽  
Pressure Sensors ◽  
Pressure Oscillation ◽  
Particle Method ◽  
Surface Flow ◽  
Particle Methods ◽  
Two Phase ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Low Pass

The sloshing phenomenon is one of the free surface flow that can endanger liquid cargo carriers such as ships. Sloshing is defined as the resonance of fluid inside a tank caused by external oscillation. When sloshing is close to the natural frequency of the tank it could endanger ships. Particle method has the advantages to be applied because sloshing is dealing with free surface. One of the particle methods is Smoothed Particle Hydrodynamics (SPH). In this study, compressible SPH was used as a result of the pressure oscillation, which exists because of the effect of density fluctuation as nature of weakly compressible SPH. To reduce pressure noise, a filtering method, Low Pass Filter,  was used to overcome pressure oscillation. Three pressure sensors were used in the sloshing experiment with a combination of motions and filling ratios. Only one pressure sensor located in the bottom was used to validate the numerical results. A set of SPH parameters were derived that fit for the sloshing problem. The SPH results show a good agreement with the experiment’s. The difference between SPH and experiment is under 1 % for sway, but a larger difference shows in roll. Low pass filter technique could reduce pressure noise, but comprehensive method needs to develop for general implementation.

Application of IMC-PID in the Hydraulic Headbox Total Pressure Control

2012 ◽  
Vol 462 ◽  
pp. 789-795
Author(s):  
Wei Tang ◽  
Xu Zhong Niu ◽  
Wen Juan Shan
Keyword(s):  
Control System ◽  
Time Constant ◽  
Total Pressure ◽  
Pressure Control ◽  
Internal Model Control ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Model Control ◽  
Low Pass ◽  
Pressure Control System

It is very difficult to obtain perfect performance to apply the conventional PID (Proportional-Integral-Derivative) controller, because hydraulic headbox needs high precision total pressure control. Transfer function of total pressure control system was identified by using the direct identification method which is based on the least square method for the first-order plus delay time model. Then combined with IMC (Internal-Model-control) –PID method, an IMC-PID controller was designed, which is simple and only needed to adjust one parameter-the time constant of low pass filter. Acceptable performance can also be obtained by tuning time constant of the low pass filter when the model doesn't match with the real process. The algorithm was applied to total pressure control system of hydraulic headbox. Simulation and practical application show that, IMC-PID is of strong robustness and good dynamic characteristics. Finally, the control system is implemented by S7-300 PLC.

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