Search results for: locus control
10846 Distribution-Free Exponentially Weighted Moving Average Control Charts for Monitoring Process Variability
Authors: Chen-Fang Tsai, Shin-Li Lu
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Distribution-free control chart is an oncoming area from the statistical process control charts in recent years. Some researchers have developed various nonparametric control charts and investigated the detection capability of these charts. The major advantage of nonparametric control charts is that the underlying process is not specifically considered the assumption of normality or any parametric distribution. In this paper, two nonparametric exponentially weighted moving average (EWMA) control charts based on nonparametric tests, namely NE-S and NE-M control charts, are proposed for monitoring process variability. Generally, weighted moving average (GWMA) control charts are extended by utilizing design and adjustment parameters for monitoring the changes in the process variability, namely NG-S and NG-M control charts. Statistical performance is also investigated on NG-S and NG-M control charts with run rules. Moreover, sensitivity analysis is performed to show the effects of design parameters under the nonparametric NG-S and NG-M control charts.Keywords: Distribution-free control chart, EWMA control charts, GWMA control charts
Procedia PDF Downloads 27510845 Model Predictive Control Using Thermal Inputs for Crystal Growth Dynamics
Authors: Takashi Shimizu, Tomoaki Hashimoto
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Recently, crystal growth technologies have made progress by the requirement for the high quality of crystal materials. To control the crystal growth dynamics actively by external forces is useuful for reducing composition non-uniformity. In this study, a control method based on model predictive control using thermal inputs is proposed for crystal growth dynamics of semiconductor materials. The control system of crystal growth dynamics considered here is governed by the continuity, momentum, energy, and mass transport equations. To establish the control method for such thermal fluid systems, we adopt model predictive control known as a kind of optimal feedback control in which the control performance over a finite future is optimized with a performance index that has a moving initial time and terminal time. The objective of this study is to establish a model predictive control method for crystal growth dynamics of semiconductor materials.Keywords: model predictive control, optimal control, process control, crystal growth
Procedia PDF Downloads 35910844 Process Capability Analysis by Using Statistical Process Control of Rice Polished Cylinder Turning Practice
Authors: S. Bangphan, P. Bangphan, T.Boonkang
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Quality control helps industries in improvements of its product quality and productivity. Statistical Process Control (SPC) is one of the tools to control the quality of products that turning practice in bringing a department of industrial engineering process under control. In this research, the process control of a turning manufactured at workshops machines. The varying measurements have been recorded for a number of samples of a rice polished cylinder obtained from a number of trials with the turning practice. SPC technique has been adopted by the process is finally brought under control and process capability is improved.Keywords: rice polished cylinder, statistical process control, control charts, process capability
Procedia PDF Downloads 48910843 Setting Control Limits For Inaccurate Measurements
Authors: Ran Etgar
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The process of rounding off measurements in continuous variables is commonly encountered. Although it usually has minor effects, sometimes it can lead to poor outcomes in statistical process control using X ̅-chart. The traditional control limits can cause incorrect conclusions if applied carelessly. This study looks into the limitations of classical control limits, particularly the impact of asymmetry. An approach to determining the distribution function of the measured parameter (Y ̅) is presented, resulting in a more precise method to establish the upper and lower control limits. The proposed method, while slightly more complex than Shewhart's original idea, is still user-friendly and accurate and only requires the use of two straightforward tables.Keywords: quality control, process control, round-off, measurement, rounding error
Procedia PDF Downloads 10010842 RAFU Functions in Robotics and Automation
Authors: Alicia C. Sanchez
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This paper investigates the implementation of RAFU functions (radical functions) in robotics and automation. Specifically, the main goal is to show how these functions may be useful in lane-keeping control and the lateral control of autonomous machines, vehicles, robots or the like. From the knowledge of several points of a certain route, the RAFU functions are used to achieve the lateral control purpose and maintain the lane-keeping errors within the fixed limits. The stability that these functions provide, their ease of approaching any continuous trajectory and the control of the possible error made on the approximation may be useful in practice.Keywords: automatic navigation control, lateral control, lane-keeping control, RAFU approximation
Procedia PDF Downloads 30310841 Model Predictive Control of Turbocharged Diesel Engine with Exhaust Gas Recirculation
Authors: U. Yavas, M. Gokasan
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Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.Keywords: predictive control, engine control, engine modeling, PID control, feedforward compensation
Procedia PDF Downloads 63710840 Killing Your Children to Hurt Your Partner: Motivations for Revenge Filicide
Authors: Melanie Moen, Christiaan Bezuidenhout
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Cases of parents murdering their offspring are incomprehensible but sadly as old as humanity itself. The act of killing your own child is known as filicide. Revenge filicide is an act where one parent kills their own offspring for retribution for hurting and upsetting the other parent. The true extent of filicide in South Africa is unknown, but in the United States, filicide constitutes more or less 2.5% of all murders. The focus of this contribution is to extend the knowledge of revenge filicide. Data was collected through court documents and newspaper articles. Newspapers that cover murder cases are between 75% to 100% accurate compared to official sources. Often family-related murders are violent in nature, and for this reason, these crimes receive extensive media coverage. The cases of twenty revenge filicide murderers (14 male and 6 female) were qualitatively analyzed to determine the motivations and offense characteristics of revenge filicide offenders. Findings related to a loss of social identity due to rejection; extreme rage-type anger; external locus of control; sadism; a desire to cause pain, and a need to inflict harm. The initial emotional response may escalate from mild anger to a level of narcissistic rage which eventually culminates in the murdering of the child to punish and hurt the other parent and to restore control. To our knowledge, our study is the first to systematically examine the motivations related to revenge filicides from a South African perspective. Filicide is a complex phenomenon with diverse possibilities and reasons why it occurs. However, it was apparent in this study that the motivations for revenge filicides were often linked to complex personal and interpersonal relationship problems. Further research within this field is imperative.Keywords: revenge filicide, child murder, rage, anger, narcissistic rage, parent kills child
Procedia PDF Downloads 8010839 On the Bootstrap P-Value Method in Identifying out of Control Signals in Multivariate Control Chart
Authors: O. Ikpotokin
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In any production process, every product is aimed to attain a certain standard, but the presence of assignable cause of variability affects our process, thereby leading to low quality of product. The ability to identify and remove this type of variability reduces its overall effect, thereby improving the quality of the product. In case of a univariate control chart signal, it is easy to detect the problem and give a solution since it is related to a single quality characteristic. However, the problems involved in the use of multivariate control chart are the violation of multivariate normal assumption and the difficulty in identifying the quality characteristic(s) that resulted in the out of control signals. The purpose of this paper is to examine the use of non-parametric control chart (the bootstrap approach) for obtaining control limit to overcome the problem of multivariate distributional assumption and the p-value method for detecting out of control signals. Results from a performance study show that the proposed bootstrap method enables the setting of control limit that can enhance the detection of out of control signals when compared, while the p-value method also enhanced in identifying out of control variables.Keywords: bootstrap control limit, p-value method, out-of-control signals, p-value, quality characteristics
Procedia PDF Downloads 34810838 The Exploitation of Balancing an Inverted Pendulum System Using Sliding Mode Control
Authors: Sheren H. Salah, Ahmed Y. Ben Sasi
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The inverted pendulum system is a classic control problem that is used in universities around the world. It is a suitable process to test prototype controllers due to its high non-linearities and lack of stability. The inverted pendulum represents a challenging control problem, which continually moves toward an uncontrolled state. This paper presents the possibility of balancing an inverted pendulum system using sliding mode control (SMC). The goal is to determine which control strategy delivers better performance with respect to pendulum’s angle and cart's position. Therefore, proportional-integral-derivative (PID) is used for comparison. Results have proven SMC control produced better response compared to PID control in both normal and noisy systems.Keywords: inverted pendulum (IP), proportional-integral derivative (PID), sliding mode control (SMC), systems and control engineering
Procedia PDF Downloads 58810837 Rounded-off Measurements and Their Implication on Control Charts
Authors: Ran Etgar
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The process of rounding off measurements in continuous variables is commonly encountered. Although it usually has minor effects, sometimes it can lead to poor outcomes in statistical process control using X ̅-chart. The traditional control limits can cause incorrect conclusions if applied carelessly. This study looks into the limitations of classical control limits, particularly the impact of asymmetry. An approach to determining the distribution function of the measured parameter (Y ̅) is presented, resulting in a more precise method to establish the upper and lower control limits. The proposed method, while slightly more complex than Shewhart's original idea, is still user-friendly and accurate and only requires the use of two straightforward tables.Keywords: inaccurate measurement, SPC, statistical process control, rounded-off, control chart
Procedia PDF Downloads 4210836 Fuzzy Logic Control for Flexible Joint Manipulator: An Experimental Implementation
Authors: Sophia Fry, Mahir Irtiza, Alexa Hoffman, Yousef Sardahi
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This study presents an intelligent control algorithm for a flexible robotic arm. Fuzzy control is used to control the motion of the arm to maintain the arm tip at the desired position while reducing vibration and increasing the system speed of response. The Fuzzy controller (FC) is based on adding the tip angular position to the arm deflection angle and using their sum as a feedback signal to the control algorithm. This reduces the complexity of the FC in terms of the input variables, number of membership functions, fuzzy rules, and control structure. Also, the design of the fuzzy controller is model-free and uses only our knowledge about the system. To show the efficacy of the FC, the control algorithm is implemented on the flexible joint manipulator (FJM) developed by Quanser. The results show that the proposed control method is effective in terms of response time, overshoot, and vibration amplitude.Keywords: fuzzy logic control, model-free control, flexible joint manipulators, nonlinear control
Procedia PDF Downloads 12110835 Genetic Association of SIX6 Gene with Pathogenesis of Glaucoma
Authors: Riffat Iqbal, Sidra Ihsan, Andleeb Batool, Maryam Mukhtar
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Glaucoma is a gathering of optic neuropathies described by dynamic degeneration of retinal ganglionic cells. It is clinically and innately heterogenous illness containing a couple of particular forms each with various causes and severities. Primary open-angle glaucoma (POAG) is the most generally perceived kind of glaucoma. This study investigated the genetic association of single nucleotide polymorphisms (SNPs; rs10483727 and rs33912345) at the SIX1/SIX6 locus with primary open-angle glaucoma (POAG) in the Pakistani population. The SIX6 gene plays an important role in ocular development and has been associated with morphology of the optic nerve. A total of 100 patients clinically diagnosed with glaucoma and 100 control individuals of age over 40 were enrolled in the study. Genomic DNA was extracted by organic extraction method. The SNP genotyping was done by (i) PCR based restriction fragment length polymorphism (RFLP) and sequencing method. Significant genetic associations were observed for rs10483727 (risk allele T) and rs33912345 (risk allele C) with POAG. Hence, it was concluded that Six6 gene is genetically associated with pathogenesis of Glaucoma in Pakistan.Keywords: genotyping, Pakistani population, primary open-angle glaucoma, SIX6 gene
Procedia PDF Downloads 18610834 PID Sliding Mode Control with Sliding Surface Dynamics based Continuous Control Action for Robotic Systems
Authors: Wael M. Elawady, Mohamed F. Asar, Amany M. Sarhan
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This paper adopts a continuous sliding mode control scheme for trajectory tracking control of robot manipulators with structured and unstructured uncertain dynamics and external disturbances. In this algorithm, the equivalent control in the conventional sliding mode control is replaced by a PID control action. Moreover, the discontinuous switching control signal is replaced by a continuous proportional-integral (PI) control term such that the implementation of the proposed control algorithm does not require the prior knowledge of the bounds of unknown uncertainties and external disturbances and completely eliminates the chattering phenomenon of the conventional sliding mode control approach. The closed-loop system with the adopted control algorithm has been proved to be globally stable by using Lyapunov stability theory. Numerical simulations using the dynamical model of robot manipulators with modeling uncertainties demonstrate the superiority and effectiveness of the proposed approach in high speed trajectory tracking problems.Keywords: PID, robot, sliding mode control, uncertainties
Procedia PDF Downloads 50910833 Fuzzy-Sliding Controller Design for Induction Motor Control
Authors: M. Bouferhane, A. Boukhebza, L. Hatab
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In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller.Keywords: linear induction motor, vector control, backstepping, fuzzy-sliding mode control
Procedia PDF Downloads 49010832 Application of Statistical Linearized Models for Investigations of Digital Dynamic Pulse-Frequency Control Systems
Authors: B. H. Aitchanov, Sh. K. Aitchanova, O. A. Baimuratov
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This paper is focused on dynamic pulse-frequency modulation (DPFM) control systems. Currently, the control law based on DPFM control signals is widely used in direct digital control subsystems introduced in the automated control systems of technological processes. Statistical analysis of automatic control systems is reduced to its construction of functional relationships between the statistical characteristics of the errors processes and input processes. Structural and dynamic Volterra models of digital pulse-frequency control systems can be used to develop methods for generating the dependencies, differing accuracy, requiring the amount of information about the statistical characteristics of input processes and computing labor intensity of their use.Keywords: digital dynamic pulse-frequency control systems, dynamic pulse-frequency modulation, control object, discrete filter, impulse device, microcontroller
Procedia PDF Downloads 49510831 Reductions of Control Flow Graphs
Authors: Robert Gold
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Control flow graphs are a well-known representation of the sequential control flow structure of programs with a multitude of applications. Not only single functions but also sets of functions or complete programs can be modelled by control flow graphs. In this case the size of the graphs can grow considerably and thus makes it difficult for software engineers to analyse the control flow. Graph reductions are helpful in this situation. In this paper we define reductions to subsets of nodes. Since executions of programs are represented by paths through the control flow graphs, paths should be preserved. Furthermore, the composition of reductions makes a stepwise analysis approach possible.Keywords: control flow graph, graph reduction, software engineering, software applications
Procedia PDF Downloads 55210830 Fast Terminal Synergetic Converter Control
Authors: Z. Bouchama, N. Essounbouli, A. Hamzaoui, M. N. Harmas
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A new robust finite time synergetic controller is presented based on recently developed synergetic control methodology and a terminal attractor technique. A Fast Terminal Synergetic Control (FTSC) is proposed for controlling DC-DC buck converter. Unlike Synergetic Control (SC) and sliding mode control, the proposed control scheme has the characteristics of finite time convergence and chattering free phenomena. Simulation of stabilization and reference tracking for buck converter systems illustrates the approach effectiveness while stability is assured in the Lyapunov sense and converse Lyapunov results involving scalar differential inequalities are given for finite-time stability.Keywords: dc-dc buck converter, synergetic control, finite time convergence, terminal synergetic control, fast terminal synergetic control, Lyapunov
Procedia PDF Downloads 46210829 Simulation and Analysis of Inverted Pendulum Controllers
Authors: Sheren H. Salah
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The inverted pendulum is a highly nonlinear and open-loop unstable system. An inverted pendulum (IP) is a pendulum which has its mass above its pivot point. It is often implemented with the pivot point mounted on a cart that can move horizontally and may be called a cart and pole. The characteristics of the inverted pendulum make identification and control more challenging. This paper presents the simulation study of several control strategies for an inverted pendulum system. The goal is to determine which control strategy delivers better performance with respect to pendulum’s angle. The inverted pendulum represents a challenging control problem, which continually moves toward an uncontrolled state. For controlling the inverted pendulum. The simulation study that sliding mode control (SMC) control produced better response compared to Genetic Algorithm Control (GAs) and proportional-integral-derivative(PID) control.Keywords: Inverted Pendulum (IP) Proportional-Integral-Derivative (PID), Genetic Algorithm Control (GAs), Sliding Mode Control (SMC)
Procedia PDF Downloads 55510828 Active Disturbance Rejection Control for Wind System Based on a DFIG
Authors: R. Chakib, A. Essadki, M. Cherkaoui
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This paper proposes the study of a robust control of the doubly fed induction generator (DFIG) used in a wind energy production. The proposed control is based on the linear active disturbance rejection control (ADRC) and it is applied to the control currents rotor of the DFIG, the DC bus voltage and active and reactive power exchanged between the DFIG and the network. The system under study and the proposed control are simulated using MATLAB/SIMULINK.Keywords: doubly fed induction generator (DFIG), active disturbance rejection control (ADRC), vector control, MPPT, extended state observer, back-to-back converter, wind turbine
Procedia PDF Downloads 48810827 Risky Driving Behavior among Bus Driver in Jakarta
Authors: Ratri A. Benedictus, Felicia M. Yolanda
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Public transport is a crucial issue for capital city in developing country, such as Jakarta. Inadequate number and low quality of public transport services resulting personal vehicles as the main option. As a result, traffic jams are getting worse in Jakarta. The low quality of public transport, particularly buses, compounded by the risk behavior of the driver. Traffic accidents involving public bus in Jakarta were often the case, even result in fatality. The purpose of this study is to get a description of risk behavior among the public bus drivers in Jakarta. 132 bus drivers become respondent of this study. Risky Driving Behavior scale of Dorn were used. Data were analyzed using descriptive statistics. 51.5% of respondents felt often showing risky behavior while on driving. The highest type of risky driving behavior is still using the unsafe bus (62%). Followed by trespass the bus line (30%), over speed (21%), violate the road signs (15%) and driving with unhealthy physical condition (4%). Results of this study suggested that high understanding of the bus drivers on their risk behaviors have not lead to the emergence of safe driving behavior. Therefore, together with technical engineering and instrumentation work intervention over this issue, psychological aspects also need to be considered, such as: risk perception, safety attitude,safety culture, locus of control and Fatalism.Keywords: bus driver, psychological factors, public transportation, risky driving behavior
Procedia PDF Downloads 36210826 Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) Control of Quadcopters: A Comparative Analysis
Authors: Anel Hasić, Naser Prljača
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In the domain of autonomous or piloted flights, the accurate control of quadrotor trajectories is of paramount significance for large numbers of tasks. These adaptable aerial platforms find applications that span from high-precision aerial photography and surveillance to demanding search and rescue missions. Among the fundamental challenges confronting quadrotor operation is the demand for accurate following of desired flight paths. To address this control challenge, among others, two celebrated well-established control strategies have emerged as noteworthy contenders: Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) control. In this work, we focus on the extensive examination of MPC and PID control techniques by using comprehensive simulation studies in MATLAB/Simulink. Intensive simulation results demonstrate the performance of the studied control algorithms.Keywords: MATLAB, MPC, PID, quadcopter, simulink
Procedia PDF Downloads 7210825 Application of Artificial Neural Networks to Adaptive Speed Control under ARDUINO
Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero
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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control
Procedia PDF Downloads 36610824 Implicit Force Control of a Position Controlled Robot - A Comparison with Explicit Algorithms
Authors: Alexander Winkler, Jozef Suchý
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This paper investigates simple implicit force control algorithms realizable with industrial robots. A lot of approaches already published are difficult to implement in commercial robot controllers, because the access to the robot joint torques is necessary or the complete dynamic model of the manipulator is used. In the past we already deal with explicit force control of a position controlled robot. Well known schemes of implicit force control are stiffness control, damping control and impedance control. Using such algorithms the contact force cannot be set directly. It is further the result of controller impedance, environment impedance and the commanded robot motion/position. The relationships of these properties are worked out in this paper in detail for the chosen implicit approaches. They have been adapted to be implementable on a position controlled robot. The behaviors of stiffness control and damping control are verified by practical experiments. For this purpose a suitable test bed was configured. Using the full mechanical impedance within the controller structure will not be practical in the case when the robot is in physical contact with the environment. This fact will be verified by simulation.Keywords: robot force control, stiffness control, damping control, impedance control, stability
Procedia PDF Downloads 52010823 Knowledge Discovery from Production Databases for Hierarchical Process Control
Authors: Pavol Tanuska, Pavel Vazan, Michal Kebisek, Dominika Jurovata
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The paper gives the results of the project that was oriented on the usage of knowledge discoveries from production systems for needs of the hierarchical process control. One of the main project goals was the proposal of knowledge discovery model for process control. Specifics data mining methods and techniques was used for defined problems of the process control. The gained knowledge was used on the real production system, thus, the proposed solution has been verified. The paper documents how it is possible to apply new discovery knowledge to be used in the real hierarchical process control. There are specified the opportunities for application of the proposed knowledge discovery model for hierarchical process control.Keywords: hierarchical process control, knowledge discovery from databases, neural network, process control
Procedia PDF Downloads 48110822 Balancing and Synchronization Control of a Two Wheel Inverted Pendulum Vehicle
Authors: Shiuh-Jer Huang, Shin-Ham Lee, Sheam-Chyun Lin
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A two wheel inverted pendulum (TWIP) vehicle is built with two hub DC motors for motion control evaluation. Arduino Nano micro-processor is chosen as the control kernel for this electric test plant. Accelerometer and gyroscope sensors are built in to measure the tilt angle and angular velocity of the inverted pendulum vehicle. Since the TWIP has significantly hub motor dead zone and nonlinear system dynamics characteristics, the vehicle system is difficult to control by traditional model based controller. The intelligent model-free fuzzy sliding mode controller (FSMC) was employed as the main control algorithm. Then, intelligent controllers are designed for TWIP balance control, and two wheels synchronization control purposes.Keywords: balance control, synchronization control, two-wheel inverted pendulum, TWIP
Procedia PDF Downloads 39710821 The Control System Architecture of Space Environment Simulator
Authors: Zhan Haiyang, Gu Miao
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This article mainly introduces the control system architecture of space environment simulator, simultaneously also briefly introduce the automation control technology of industrial process and the measurement technology of vacuum and cold black environment. According to the volume of chamber, the space environment simulator is divided into three types of small, medium and large. According to the classification and application of space environment simulator, the control system is divided into the control system of small, medium, large space environment simulator and the centralized control system of multiple space environment simulators.Keywords: space environment simulator, control system, architecture, automation control technology
Procedia PDF Downloads 47510820 Supply Air Pressure Control of HVAC System Using MPC Controller
Authors: P. Javid, A. Aeenmehr, J. Taghavifar
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In this paper, supply air pressure of HVAC system has been modeled with second-order transfer function plus dead-time. In HVAC system, the desired input has step changes, and the output of proposed control system should be able to follow the input reference, so the idea of using model based predictive control is proceeded and designed in this paper. The closed loop control system is implemented in MATLAB software and the simulation results are provided. The simulation results show that the model based predictive control is able to control the plant properly.Keywords: air conditioning system, GPC, dead time, air supply control
Procedia PDF Downloads 52710819 Stochastic Model Predictive Control for Linear Discrete-Time Systems with Random Dither Quantization
Authors: Tomoaki Hashimoto
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Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.Keywords: optimal control, stochastic systems, random dither, quantization
Procedia PDF Downloads 44610818 Research on Robot Adaptive Polishing Control Technology
Authors: Yi Ming Zhang, Zhan Xi Wang, Hang Chen, Gang Wang
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Manual polishing has problems such as high labor intensity, low production efficiency and difficulty in guaranteeing the consistency of polishing quality. It is more and more necessary to replace manual polishing with robot polishing. Polishing force directly affects the quality of polishing, so accurate tracking and control of polishing force is one of the most important conditions for improving the accuracy of robot polishing. The traditional force control strategy is difficult to adapt to the strong coupling of force control and position control during the robot polishing process. Therefore, based on the analysis of force-based impedance control and position-based impedance control, this paper proposed a new type of adaptive controller. Based on force feedback control of active compliance control, the controller can adaptively estimate the stiffness and position of the external environment and eliminate the steady-state force error produced by traditional impedance control. The simulation results of the model shows that the adaptive controller has good adaptability to changing environmental positions and environmental stiffness, and can accurately track and control polishing force.Keywords: robot polishing, force feedback, impedance control, adaptive control
Procedia PDF Downloads 20110817 Particle Swarm Optimisation of a Terminal Synergetic Controllers for a DC-DC Converter
Authors: H. Abderrezek, M. N. Harmas
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DC-DC converters are widely used as reliable power source for many industrial and military applications, computers and electronic devices. Several control methods were developed for DC-DC converters control mostly with asymptotic convergence. Synergetic control (SC) is a proven robust control approach and will be used here in a so-called terminal scheme to achieve finite time convergence. Lyapunov synthesis is adopted to assure controlled system stability. Furthermore particle swarm optimization (PSO) algorithm, based on an integral time absolute of error (ITAE) criterion will be used to optimize controller parameters. Simulation of terminal synergetic control of a DC-DC converter is carried out for different operating conditions and results are compared to classic synergetic control performance, that which demonstrate the effectiveness and feasibility of the proposed control method.Keywords: DC-DC converter, PSO, finite time, terminal, synergetic control
Procedia PDF Downloads 503