scholarly journals A Real-Time Realization Method for the Pneumatic Positioning System of the Industrial Automated Production Line Using Low-Cost On–Off Valves

Actuators ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 260
Author(s):  
Zhonglin Lin ◽  
Qi Xie ◽  
Qiang Qian ◽  
Tianhong Zhang ◽  
Jiaming Zhang ◽  
...  
Keyword(s):  
Steady State ◽  
Real Time ◽  
Production Line ◽  
Sliding Mode ◽  
Low Cost ◽  
Control Period ◽  
System Stability ◽  
Step Response ◽  
Automated Production ◽  
State Error

In the industrial automated production line, how to use the existing low-cost pneumatic equipment to obtain the best positioning effect has become a significant engineering problem. In this paper, a differential switching method is proposed in a pneumatic servo system consisting of four low-cost on–off valves for more precise control and lower prices. All valves are simultaneously open at the initial stage of each control period, and the differential closing time of the desired valves is calculated through the theoretical models. A sliding mode controller is applied with the proposed method, and the system stability is proven. The real-time control setup including three software layers is proposed to implement the algorithm. Several experiments are performed on a real-time embedded controller. Average 0.83% overshoot and 0.18 mm steady-state error are observed in the step response experiment. The highest frequency of sine wave that can be tracked is 1 Hz, and the average error is 1.68 mm. The maximum steady-state error is about 0.5 mm in the step response under payloads of 5.25 kg. All the simulation and experimental results prove the effectiveness of the control method.

scholarly journals Kendali Kecepatan Motor Induksi 3 Fase Berbasis Particle Swarm Optimization (PSO)

2020 ◽  
Vol 8 (3) ◽  
pp. 477
Author(s):  
HANIF HASYIER FAKHRUDDIN ◽  
HANDRI TOAR ◽  
ERA PURWANTO ◽  
HARY OKTAVIANTO ◽  
RADEN AKBAR NUR APRIYANTO ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Steady State ◽  
Real Time ◽  
Induction Motor ◽  
Rise Time ◽  
Low Cost ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Scalar Control ◽  
State Error

ABSTRAKMotor induksi secara struktur dan kendali standarnya dirancang untuk bekerja pada kecepatan nominal, sehingga sulit mengendalikan kecepatan sesuai kebutuhan karena akan mengubah konstruksi motor. Penelitian tentang pengendalian motor induksi agar semudah mengendalikan motor DC sudah banyak dilakukan oleh peneliti, salah satunya adalah dengan kendali skalar. Kendali skalar banyak digunakan karena memiliki keunggulan sederhana, biaya murah, mudah didesain dan diimplementasikan, serta yang paling penting tidak memerlukan parameter dari motor induksi. Penggunaan kendali skalar yang telah dilengkapi pengendali PID penalaan otomatis, dengan parameter yang telah dioptimalkan algoritma Particle Swarm Optimization (PSO), akan memudahkan pengendalian kecepatan motor induksi tiga fase pada kecepatan beragam. Simulasi penalaan otomatis PID menggunakan PSO telah dilakukan dengan LabView, dengan karakteristik maksimal 10% overshoot, 1% error steady state dan rise time kurang dari 2 milidetik. Sementara dalam pengujian real time dengan MyRIO hasilnya tanpa overshoot, 5.5% error steady state maksimal dan rise time maksimal 5 detik.Kata kunci: Kendali skalar, PID, Particle Swarm Optimization, LabView ABSTRACTInduction motor is designed at nominal speed as default, we have to change its stucture to obtain dessired speed. Many researchers developt method how to control induction motor as simple as DC motor, one of the methods is scalar control. Scalar control has several benefits, such as simply, low cost, easily designed and implemented, and the main banefit is no necessary motor parameters. Using scalar control with PID controller that optimized Partical Swarm Optimization (PSO) algoritm, will ease to control 3 phase induction motor variant speed. Simulation auto tunning using PSO has done on LabView, it has some characteristic, they are 10% overshoot, 1% steady state error, and rise time within 2ms. In other hand, real time test using MyRIO got no overshoot, 5.5% steady state error maximal, and rise time maximal 5 s characteristic.Keywords: Scalar control, PID, Particle Swarm Optimization, LabView

scholarly journals Study and Application of Intelligent Sliding Mode Control for Voltage Source Inverters

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2544 ◽  
Author(s):  
En-Chih Chang
Keyword(s):  
Steady State ◽  
Sliding Mode Control ◽  
Digital Signal Processor ◽  
Sliding Mode ◽  
Transient Behavior ◽  
Voltage Source ◽  
Accurate Estimation ◽  
Inference System ◽  
Mode Control ◽  
State Error

In this paper, an intelligent sliding mode controlled voltage source inverter (VSI) is developed to achieve not only quick transient behavior, but satisfactory steady-state response. The presented approach combines the respective merits of a nonsingular fast terminal attractor (NFTA) as well as an adaptive neuro-fuzzy inference system (ANFIS). The NFTA allows no singularity and error states to be converged to the equilibrium within a finite time, while conventional sliding mode control (SMC) leads to long-term (infinite) convergent behavior. However, there is the likelihood of chattering or steady-state error occurring in NFTA due to the overestimation or underestimation of system uncertainty bound. The ANFIS with accurate estimation and the ease of implementation is employed in NFTA for suppressing the chatter or steady-state error so as to improve the system’s robustness against uncertain disturbances. Simulation results display that this described approach yields low distorted output wave shapes and quick transience in the presence of capacitor input rectifier loading as well as abrupt connection of linear loads. Experimental results conducted on a 1 kW VSI prototype with control algorithm implementation in Texas Instruments DSP (digital signal processor) support the theoretic analysis and reaffirm the robust performance of the developed VSI. Because the proposed VSI yields remarkable benefits over conventional terminal attractor VSIs on the basis of computational quickness and unsophisticated realization, the presented approach is a noteworthy referral to the designers of correlated VSI applications in future, such as DC (direct current) microgrids and AC (alternating current) microgrids, or even hybrid AC/DC microgrids.

scholarly journals Model Penahan Ketinggian Quadrotor Berbasis PID dengan Jaringan Syaraf Tiruan Propagasi Mundur

2021 ◽  
Vol 10 (2) ◽  
pp. 156-162
Author(s):  
Faisal Fajri Rahani ◽  
Dinan Yulianto
Keyword(s):  
Steady State ◽  
Real Time ◽  
Unmanned Aerial Vehicle ◽  
Rise Time ◽  
Settling Time ◽  
Aerial Vehicle ◽  
State Error

Quadrotor adalah salah satu jenis Unmanned Aerial Vehicle (UAV) atau wahana terbang tanpa awak yang dapat terbang dengan kendali jarak jauh maupun menggunakan kendali otomatis. Dalam melakukan misinya, quadrotor memerlukan sistem kendali yang baik. Salah satu sistem kendali dalam sistem quadrotor adalah sistem kendali ketinggian. Kendali ketinggian akan mengendalikan quadrotor seusai ketinggian yang diinginkan walaupun terdapat gangguan dan beban quadrotor itu sendiri. Metode kendali yang banyak digunakan adalah kendali PID. Kendali PID menghasilkan respons yang kurang baik karena konstanta PID yang bersifat tetap, sedangkan gangguan saat quadrotor terbang akan berubah-ubah. Oleh karena itu, makalah ini menawarkan kendali yang dapat menyesuaikan diri saat terkena gangguan tertentu. Metode yang ditawarkan adalah kendali PID dengan Jaringan Saraf Tiruan (JST). Sistem JST akan menala komponen PID secara real-time sesuai gangguan yang terjadi. Penggunaan PID dengan JST menghasilkan respons rise time lebih cepat 0,0594 detik, overshoot turun 7,58%, steady state error turun ±0,0672, dan settling time turun 1,031 detik dibandingkan dengan PID konvensional. Hal ini menunjukkan bahwa PID dengan JST menghasilkan respons kendali yang lebih baik dibandingkan dengan PID saja.

Integral Sliding Mode Control Based on Barrier Function for Servo Actuator with Friction

2021 ◽  
Vol 39 (2A) ◽  
pp. 248-259
Author(s):  
Anmar F. Abd ◽  
Shibly A. Al-Samarraie
Keyword(s):  
Steady State ◽  
Sliding Mode Control ◽  
Barrier Function ◽  
Sliding Mode ◽  
Function Parameter ◽  
Integral Sliding Mode Control ◽  
Integral Sliding Mode ◽  
Mode Control ◽  
Servo Actuator ◽  
State Error

This paper proposes the use of the integral sliding mode control (ISMC) based on the barrier function to control the servo actuator system with friction.  Based on the barrier function, the main features of the ISMC design were preserved, additionally, the proposed control design is done without the need to know the bound on the system model uncertainty, accordingly, the overestimation of the control gain doesn’t take place and the chattering is eliminated. Moreover, the steady-state error can be adjusted via selecting the barrier function parameter only. The simulation results demonstrate the performance of the proposed ISMC based on the barrier function where the system angle successfully follows the desired angular position with a small pre-adjusted steady-state error. Additionally, the obtained results clarify superior features compared with a traditional ISMC designed to the same actuator.

Real-Time Digital Simulation and Analysis of Sliding Mode and P&O MPPT Algorithms for a PV System

2015 ◽  
Vol 16 (4) ◽  
pp. 313-322 ◽  
Author(s):  
Venkata Ratnam Kolluru ◽  
Kamalakanta Mahapatra ◽  
Bidyadhar Subudhi
Keyword(s):  
Steady State ◽  
Real Time ◽  
Sliding Mode ◽  
Boost Converter ◽  
Maximum Power ◽  
Sliding Mode Controller ◽  
Step Size ◽  
Pv System ◽  
Steady State Condition ◽  
Power Extraction

Abstract This paper presents an integral Sliding Mode Controller (SMC) of a DC-DC boost converter integrated with a photovoltaic (PV) system for maximum power extraction. In view of improving the steady-state performance of the maximum power point tracking (MPPT), an integral of the error term is included in the sliding surface. The output of PV panels is connected to a DC-DC boost converter to regulate and enhance the voltage up to a desired level. By using SMC with integral term, the steady-state condition is obtained at less than 0.1 sec. With the proposed ISMC MPPT the maximum power extracted is more than 10% than the traditional Perturb & Observe (P&O) MPPT at standard test conditions (STC). The results obtained using the SMC are compared with that of the fixed step size P&O MPPT controller. The performances of the proposed sliding mode controller and the P&O controller are validated through experimentations using a Real-Time Digital Simulator (RTDS)-Opal RT.

scholarly journals Perancangan Pengendalian Kecepatan Motor Induksi Tiga Fasa Pada Mesin Sentrifugal Dengan Pendekatan Model Viteckova Orde Dua Menggunakan Metode Hybridfuzzy-SMC

2018 ◽  
Vol 15 (2) ◽  
pp. 138
Author(s):  
Ahmad Faizal
Keyword(s):  
Steady State ◽  
Induction Motor ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Response Analysis ◽  
Transient Time ◽  
Fuzzy Controllers ◽  
Non Linear ◽  
Non Linear System ◽  
State Error

Induction motor has a weakness in the speed settings, the speed will change when there is a change in load or control signal disturbance, it takes a controller that is able to overcome the shortcomings of the induction motor, one of the controller is fuzzy. Fuzzy controllers have the advantage of modeling a complex non-linear function. But fuzzy controllers have weaknesses in the form of overshoot and system oscillation. One of the controllers that is able to overcome the weakness of overshoot and oscillation of the system from the fuzzy controller is the Sliding Mode Control (SMC) controller. SMC has the advantage of being robust and able to work on non-linear system systems that have model or parameter uncertainty. Based on simulation results from fuzzy hybrid controller and SMC able to cover the weakness of fuzzy and robust controller in overcoming the load and disturbance changes. Proven with time response analysis on overshoot and steady state error better than fuzzy controller with longer transient time value at maximum load with steady state error 0,0085 Rpm with Maximum overshoot 0,38% and without system oscillation. 

scholarly journals Optimizing the Parameters of Sliding Mode Controllers for Stepper Motor through Simulink Response Optimizer Application

2021 ◽  
Vol 1 (2) ◽  
pp. 209-225
Author(s):  
Magdi Sadek Mahmoud ◽  
Ali H. AlRamadhan
Keyword(s):  
Steady State ◽  
Sliding Mode ◽  
Open Loop ◽  
Step Response ◽  
Stepper Motor ◽  
Model Parameters ◽  
Response Requirement ◽  
Load Torque ◽  
Sliding Mode Controllers ◽  
Motor Model

This paper will focus on optimizing parameters of sliding mode controllers (SMC) for hybrid stepper motor models simulated in Matlab/Simulink. The main objective is to achieve a smooth transient and robust, steady-state to track reference rotor position when the stepper motor is subjected to load disturbances. Two different structures of SMC controllers will be studied, which are based on the flat system concept that is applicable to the stepper motor model. The hassle to determine controller parameters will be optimized using the Simulink Response Optimizer application.  The performance of the controllers will be evaluated by considering load torque and variation in the model parameters. Although the results showed that an open-loop controller could move the rotor to the desired position, however, the transient response had undesired oscillations before the output settled at the steady state. The response was improved by optimizing SMC controllers’ parameters to meet the desire step response requirement. Despite both SMC methods have successfully tracked the reference, there are some challenges to deal with each method in regard to the state measurements, the number of optimized controllers’ parameters, and the scattering of control inputs.

A Novel Intelligent Learning Control Scheme for Discrete-Time Nonlinear Uncertain Systems in Multiple Environments

2020 ◽  
Author(s):  
Jingting Zhang ◽  
Chengzhi Yuan ◽  
Paolo Stegagno
Keyword(s):  
Real Time ◽  
Discrete Time ◽  
Uncertain Systems ◽  
Sliding Mode ◽  
System Stability ◽  
Recognition Mechanism ◽  
Deterministic Learning ◽  
Control Scheme ◽  
Nonlinear Uncertain Systems ◽  
Multiple Environments

Abstract In this paper, we propose a novel intelligent control scheme for a class of discrete-time nonlinear uncertain systems operating under multiple environments/control situations. First, based on the deterministic learning theory, artificial neural networks (NNs) are employed to accurately learn/identify the uncertain system dynamics under each individual environment. The learned knowledge is then utilized to: (i) achieve improved control performance by developing a family of experience-based controllers (EBCs), each of which is tailored to an individual environment; and (ii) determine real-time activation of the EBCs by developing a pattern recognition mechanism for online identifying the active control situation. In addition, a robust quasi-sliding mode controller is further designed and embedded in the overall control scheme to guarantee system stability during the transition process among multiple environments. The novelty of the proposed control scheme lies in its intelligent capabilities of knowledge acquisition and re-utilization in real-time control, enabling self-adaption to uncertain changing control environments. A simulation example is included to verify the effectiveness of the proposed results.

Verifying and Simulating of the Novel Analytical Method of the Steady-State Error for Nonunity Feedback Control Systems

2011 ◽  
Vol 301-303 ◽  
pp. 1670-1675 ◽  
Author(s):  
Shann Chyi Mou
Keyword(s):  
Control System ◽  
Steady State ◽  
Feedback Control ◽  
Error Function ◽  
Step Response ◽  
Type Number ◽  
Feedback Control System ◽  
Feedback Control Systems ◽  
Definition Of ◽  
State Error

Traditionally, the first step to analyze the steady-state error of nonunity feedback control system is to convert the system into an equivalent unity feedback control system, and calculate the steady-state error by using the concept of type number for unity feedback control system. In 2011, Mou is based on the concept of old type number and the definition of new steady-state error functione(t)=(1/KH)r(t)-y(t) by Kuo to offer the method for calculating the steady-state error of nonunity feedback control system. In this paper, three typical examples will be analyzed by the calculation of step response and by the simulation of Matlab. Therefore, we can prove that the definition of new steady-state error function e(t)=(1/KH)r(t)-y(t) by Kuo and the concept of old type number are useful to solve the steady-state error of nonunity feedback control system.

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