Search results for: Controller design for MIMOS II
5046 Adaptive Integral Backstepping Motion Control for Inverted Pendulum
Authors: Ö. Tolga Altınöz
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The adaptive backstepping controller for inverted pendulum is designed by using the general motion control model. Backstepping is a novel nonlinear control technique based on the Lyapunov design approach, used when higher derivatives of parameter estimation appear. For easy parameter adaptation, the mathematical model of the inverted pendulum converted into the motion control model. This conversion is performed by taking functions of unknown parameters and dynamics of the system. By using motion control model equations, inverted pendulum is simulated without any information about not only parameters but also measurable dynamics. Also these results are compare with the adaptive backstepping controller which extended with integral action that given from [1].
Keywords: Adaptive backstepping, inverted pendulum, nonlinear adaptive control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34905045 Torque Ripple Minimization in Switched Reluctance Motor Using Passivity-Based Robust Adaptive Control
Authors: M.M. Namazi, S.M. Saghaiannejad, A. Rashidi
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In this paper by using the port-controlled Hamiltonian (PCH) systems theory, a full-order nonlinear controlled model is first developed. Then a nonlinear passivity-based robust adaptive control (PBRAC) of switched reluctance motor in the presence of external disturbances for the purpose of torque ripple reduction and characteristic improvement is presented. The proposed controller design is separated into the inner loop and the outer loop controller. In the inner loop, passivity-based control is employed by using energy shaping techniques to produce the proper switching function. The outer loop control is employed by robust adaptive controller to determine the appropriate Torque command. It can also overcome the inherent nonlinear characteristics of the system and make the whole system robust to uncertainties and bounded disturbances. A 4KW 8/6 SRM with experimental characteristics that takes magnetic saturation into account is modeled, simulation results show that the proposed scheme has good performance and practical application prospects.Keywords: Switched Reluctance Motor, Port HamiltonianSystem, Passivity-Based Control, Torque Ripple Minimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16795044 Adaptive Fuzzy Control of Stewart Platform under Actuator Saturation
Authors: Dongsu Wu, Hongbin Gu, Peng Li
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A novel adaptive fuzzy trajectory tracking algorithm of Stewart platform based motion platform is proposed to compensate path deviation and degradation of controller-s performance due to actuator torque limit. The algorithm can be divided into two parts: the real-time trajectory shaping part and the joint space adaptive fuzzy controller part. For a reference trajectory in task space whenever any of the actuators is saturated, the desired acceleration of the reference trajectory is modified on-line by using dynamic model of motion platform. Meanwhile an additional action with respect to the difference between the nominal and modified trajectories is utilized in the non-saturated region of actuators to reduce the path error. Using modified trajectory as input, the joint space controller incorporates compute torque controller, leg velocity observer and fuzzy disturbance observer with saturation compensation. It can ensure stability and tracking performance of controller in present of external disturbance and position only measurement. Simulation results verify the effectiveness of proposed control scheme.
Keywords: Actuator saturation, adaptive fuzzy control, Stewartplatform, trajectory shaping, flight simulator
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20315043 Active Power Flow Control Using A TCSC Based Backstepping Controller in Multimachine Power System
Authors: Naimi Abdelhamid, Othmane Abdelkhalek
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With the current rise in the demand of electrical energy, present-day power systems which are large and complex, will continue to grow in both size and complexity. Flexible AC Transmission System (FACTS) controllers provide new facilities, both in steady state power flow control and dynamic stability control. Thyristor Controlled Series Capacitor (TCSC) is one of FACTS equipment, which is used for power flow control of active power in electric power system and for increase of capacities of transmission lines. In this paper, a Backstepping Power Flow Controller (BPFC) for TCSC in multimachine power system is developed and tested. The simulation results show that the TCSC proposed controller is capable of controlling the transmitted active power and improving the transient stability when compared with conventional PI Power Flow Controller (PIPFC).
Keywords: FACTS, Thyristor Controlled Series Capacitor (TCSC), Backstepping, BPFC, PIPFC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17945042 Neural Network Supervisory Proportional-Integral-Derivative Control of the Pressurized Water Reactor Core Power Load Following Operation
Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu
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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.
Keywords: machine learning, neural network, pressurized water reactor, supervisory controller
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5145041 Fuzzy Logic Speed Controller for Direct Vector Control of Induction Motor
Authors: Ben Hamed M., Sbita L
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This paper presents a new method for the implementation of a direct rotor flux control (DRFOC) of induction motor (IM) drives. It is based on the rotor flux components regulation. The d and q axis rotor flux components feed proportional integral (PI) controllers. The outputs of which are the target stator voltages (vdsref and vqsref). While, the synchronous speed is depicted at the output of rotor speed controller. In order to accomplish variable speed operation, conventional PI like controller is commonly used. These controllers provide limited good performances over a wide range of operations even under ideal field oriented conditions. An alternate approach is to use the so called fuzzy logic controller. The overall investigated system is implemented using dSpace system based on digital signal processor (DSP). Simulation and experimental results have been presented for a one kw IM drives to confirm the validity of the proposed algorithms.Keywords: DRFOC, fuzzy logic, variable speed drives, control, IM and real time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19215040 Performance Evaluation of Hybrid Intelligent Controllers in Load Frequency Control of Multi Area Interconnected Power Systems
Authors: Surya Prakash, Sunil Kumar Sinha
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This paper deals with the application of artificial neural network (ANN) and fuzzy based Adaptive Neuro Fuzzy Inference System(ANFIS) approach to Load Frequency Control (LFC) of multi unequal area hydro-thermal interconnected power system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Area-1 and area-2 consists of thermal reheat power plant whereas area-3 and area-4 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent controller like ANFIS, ANN and Fuzzy controllers and conventional PI and PID control approaches. To enhance the performance of intelligent and conventional controller sliding surface is included. The performances of the controllers are simulated using MATLAB/SIMULINK package. A comparison of ANFIS, ANN, Fuzzy, PI and PID based approaches shows the superiority of proposed ANFIS over ANN & fuzzy, PI and PID controller for 1% step load variation.Keywords: Load Frequency Control (LFC), ANFIS, ANN & Fuzzy, PI, PID Controllers, Area Control Error (ACE), Tie-line, MATLAB / SIMULINK.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36605039 Fuzzy Logic Control of Static Var Compensator for Power System Damping
Authors: N.Karpagam, D.Devaraj
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Static Var Compensator (SVC) is a shunt type FACTS device which is used in power system primarily for the purpose of voltage and reactive power control. In this paper, a fuzzy logic based supplementary controller for Static Var Compensator (SVC) is developed which is used for damping the rotor angle oscillations and to improve the transient stability of the power system. Generator speed and the electrical power are chosen as input signals for the Fuzzy Logic Controller (FLC). The effectiveness and feasibility of the proposed control is demonstrated with Single Machine Infinite Bus (SMIB) system and multimachine system (WSCC System) which show improvement over the use of a fixed parameter controller.Keywords: FLC, SVC, Transient stability, SMIB, PIDcontroller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34455038 Biologically Inspired Controller for the Autonomous Navigation of a Mobile Robot in an Evasion Task
Authors: Dejanira Araiza-Illan, Tony J. Dodd
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A novel biologically inspired controller for the autonomous navigation of a mobile robot in an evasion task is proposed. The controller takes advantage of the environment by calculating a measure of danger and subsequently choosing the parameters of a reinforcement learning based decision process. Two different reinforcement learning algorithms were used: Qlearning and Sarsa (λ). Simulations show that selecting dynamic parameters reduce the time while executing the decision making process, so the robot can obtain a policy to succeed in an escaping task in a realistic time.Keywords: Autonomous navigation, mobile robots, reinforcement learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14795037 Generalized Predictive Control of Batch Polymerization Reactor
Authors: R. Khaniki, M.B. Menhaj, H. Eliasi
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This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.
Keywords: Generalized Predictive Control (GPC), TemperatureControl, Global Linearizing Control (GLC), Batch Reactor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15035036 Generalized Predictive Control of Batch Polymerization Reactor
Authors: R. Khaniki, M.B. Menhaj, H. Eliasi
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This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.Keywords: Generalized Predictive Control (GPC), TemperatureControl, Global Linearizing Control (GLC), Batch Reactor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17815035 A Predictive control based on Neural Network for Proton Exchange Membrane Fuel Cell
Authors: M. Sedighizadeh, M. Rezaei, V. Najmi
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The Proton Exchange Membrane Fuel Cell (PEMFC) control system has an important effect on operation of cell. Traditional controllers couldn-t lead to acceptable responses because of time- change, long- hysteresis, uncertainty, strong- coupling and nonlinear characteristics of PEMFCs, so an intelligent or adaptive controller is needed. In this paper a neural network predictive controller have been designed to control the voltage of at the presence of fluctuations of temperature. The results of implementation of this designed NN Predictive controller on a dynamic electrochemical model of a small size 5 KW, PEM fuel cell have been simulated by MATLAB/SIMULINK.Keywords: PEMFC, Neural Network, Predictive Control..
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26195034 Fuzzy Sliding Mode Control of an MR Mount for Vibration Attenuation
Authors: Jinsiang Shaw, Ray Pan, Yin-Chieh Chang
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In this paper, an magnetorheological (MR) mount with fuzzy sliding mode controller (FSMC) is studied for vibration suppression when the system is subject to base excitations. In recent years, magnetorheological fluids are becoming a popular material in the field of the semi-active control. However, the dynamic equation of an MR mount is highly nonlinear and it is difficult to identify. FSMC provides a simple method to achieve vibration attenuation of the nonlinear system with uncertain disturbances. This method is capable of handling the chattering problem of sliding mode control effectively and the fuzzy control rules are obtained by using the Lyapunov stability theory. The numerical simulations using one-dimension and two-dimension FSMC show effectiveness of the proposed controller for vibration suppression. Further, the well-known skyhook control scheme and an adaptive sliding mode controller are also included in the simulation for comparison with the proposed FSMC.Keywords: adaptive sliding mode controller, fuzzy sliding modecontroller, magnetorheological mount, skyhook control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17945033 Fuzzy Separation Bearing Control for Mobile Robots Formation
Authors: A. Bazoula, H. Maaref
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In this article we address the problem of mobile robot formation control. Indeed, the most work, in this domain, have studied extensively classical control for keeping a formation of mobile robots. In this work, we design an FLC (Fuzzy logic Controller) controller for separation and bearing control (SBC). Indeed, the leader mobile robot is controlled to follow an arbitrary reference path, and the follower mobile robot use the FSBC (Fuzzy Separation and Bearing Control) to keep constant relative distance and constant angle to the leader robot. The efficiency and simplicity of this control law has been proven by simulation on different situation.
Keywords: Autonomous mobile robot, Formation control, Fuzzy logic control, Multiple robots, Leader-Follower.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17235032 Hand Motion and Gesture Control of Laboratory Test Equipment Using the Leap Motion Controller
Authors: Ian A. Grout
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In this paper, the design and development of a system to provide hand motion and gesture control of laboratory test equipment is considered and discussed. The Leap Motion controller is used to provide an input to control a laboratory power supply as part of an electronic circuit experiment. By suitable hand motions and gestures, control of the power supply is provided remotely and without the need to physically touch the equipment used. As such, it provides an alternative manner in which to control electronic equipment via a PC and is considered here within the field of human computer interaction (HCI).
Keywords: Control, hand gesture, human computer interaction, test equipment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9765031 Stability Improvement of AC System by Controllability of the HVDC
Authors: Omid Borazjani, Alireza Rajabi, Mojtaba Saeedimoghadam, Khodakhast Isapour
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High Voltage Direct Current (HVDC) power transmission is employed to move large amounts of electric power. There are several possibilities to enhance the transient stability in a power system. One adequate option is by using the high controllability of the HVDC if HVDC is available in the system. This paper presents a control technique for HVDC to enhance the transient stability. The strategy controls the power through the HVDC to help make the system more transient stable during disturbances. Loss of synchronism is prevented by quickly producing sufficient decelerating energy to counteract accelerating energy gained during. In this study, the power flow in the HVDC link is modulated with the addition of an auxiliary signal to the current reference of the rectifier firing angle controller. This modulation control signal is derived from speed deviation signal of the generator utilizing a PD controller; the utilization of a PD controller is suitable because it has the property of fast response. The effectiveness of the proposed controller is demonstrated with a SMIB test system.Keywords: HVDC, SMIB, Stability, Power System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23355030 Application of PSO Technique for Seismic Control of Tall Building
Authors: A. Shayeghi, H. Shayeghi, H. Eimani Kalasar
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In recent years, tuned mass damper (TMD) control systems for civil engineering structures have attracted considerable attention. This paper emphasizes on the application of particle swarm application (PSO) to design and optimize the parameters of the TMD control scheme for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using the PSO technique which has a story ability to find the most optimistic results. An 11- story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed method. The results analysis through the time-domain simulation and some performance indices reveals that the designed PSO based TMD controller has an excellent capability in reduction of the seismically excited example building.
Keywords: TMD, Particle Swarm Optimization, Tall Buildings, Structural Dynamics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18185029 Enhance the Modeling of BLDC Motor Based on Fuzzy Logic
Authors: Murugan Marimuthu, Jeyabharath Rajaih
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This paper describes a simple way to control the speed of PMBLDC motor using Fuzzy logic control method. In the conventional PI controller the performance of the motor system is simulated and the speed is regulated by using PI controller. These methods used to improve the performance of PMSM drives, but in some cases at different operating conditions when the dynamics of the system also vary over time and it can change the reference speed, parameter variations and the load disturbance. The simulation is powered with the MATLAB program to get a reliable and flexible simulation. In order to highlight the effectiveness of the speed control method the FLC method is used. The proposed method targeted in achieving the improved dynamic performance and avoids the variations of the motor drive. This drive has high accuracy, robust operation from near zero to high speed. The effectiveness and flexibility of the individual techniques of the speed control method will be thoroughly discussed for merits and demerits and finally verified through simulation and experimental results for comparative analysis.Keywords: Hall position sensors, permanent magnet brushless DC motor, PI controller, Fuzzy Controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17855028 Online Robust Model Predictive Control for Linear Fractional Transformation Systems Using Linear Matrix Inequalities
Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper
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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l2-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.
Keywords: Linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12945027 Modeling and Design of MPPT Controller Using Stepped P&O Algorithm in Solar Photovoltaic System
Authors: R. Prakash, B. Meenakshipriya, R. Kumaravelan
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This paper presents modeling and simulation of Grid Connected Photovoltaic (PV) system by using improved mathematical model. The model is used to study different parameter variations and effects on the PV array including operating temperature and solar irradiation level. In this paper stepped P&O algorithm is proposed for MPPT control. This algorithm will identify the suitable duty ratio in which the DC-DC converter should be operated to maximize the power output. Photo voltaic array with proposed stepped P&O-MPPT controller can operate in the maximum power point for the whole range of solar data (irradiance and temperature).
Keywords: Photovoltaic (PV), Maximum Power Point Tracking (MPPT), Boost converter, Stepped Perturb & Observe method (Stepped P&O).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40115026 Simultaneous Tuning of Static Var Compensator and Power System Stabilizer Employing Real- Coded Genetic Algorithm
Authors: S. Panda, N. P. Patidar, R. Singh
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Power system stability enhancement by simultaneous tuning of a Power System Stabilizer (PSS) and a Static Var Compensator (SVC)-based controller is thoroughly investigated in this paper. The coordination among the proposed damping stabilizers and the SVC internal voltage regulators has also been taken into consideration. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and Real-Coded Genetic Algorithm (RCGA) is employed to search for optimal controller parameters. The proposed stabilizers are tested on a weakly connected power system with different disturbances and loading conditions. The nonlinear simulation results are presented to show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.
Keywords: Real-Coded Genetic Algorithm (RCGA), Static Var Compensator (SVC), Power System Stabilizer (PSS), Low Frequency Oscillations, Power System Stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22545025 Limit Cycle Behaviour of a Neural Controller with Delayed Bang-Bang Feedback
Authors: Travis Wiens, Greg Schoenau, Rich Burton
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It is well known that a linear dynamic system including a delay will exhibit limit cycle oscillations when a bang-bang sensor is used in the feedback loop of a PID controller. A similar behaviour occurs when a delayed feedback signal is used to train a neural network. This paper develops a method of predicting this behaviour by linearizing the system, which can be shown to behave in a manner similar to an integral controller. Using this procedure, it is possible to predict the characteristics of the neural network driven limit cycle to varying degrees of accuracy, depending on the information known about the system. An application is also presented: the intelligent control of a spark ignition engine.Keywords: Control and automation, artificial neural networks, limit cycle
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12775024 Designing a Robust Controller for a 6 Linkage Robot
Authors: G. Khamooshian
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One of the main points of application of the mechanisms of the series and parallel is the subject of managing them. The control of this mechanism and similar mechanisms is one that has always been the intention of the scholars. On the other hand, modeling the behavior of the system is difficult due to the large number of its parameters, and it leads to complex equations that are difficult to solve and eventually difficult to control. In this paper, a six-linkage robot has been presented that could be used in different areas such as medical robots. Using these robots needs a robust control. In this paper, the system equations are first found, and then the system conversion function is written. A new controller has been designed for this robot which could be used in other parallel robots and could be very useful. Parallel robots are so important in robotics because of their stability, so methods for control of them are important and the robust controller, especially in parallel robots, makes a sense.
Keywords: 3-RRS, 6 linkage, parallel robot, control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6695023 Genetic Algorithm Based Optimal Control for a 6-DOF Non Redundant Stewart Manipulator
Authors: A. Omran, G. El-Bayiumi, M. Bayoumi, A. Kassem
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Applicability of tuning the controller gains for Stewart manipulator using genetic algorithm as an efficient search technique is investigated. Kinematics and dynamics models were introduced in detail for simulation purpose. A PD task space control scheme was used. For demonstrating technique feasibility, a Stewart manipulator numerical-model was built. A genetic algorithm was then employed to search for optimal controller gains. The controller was tested onsite a generic circular mission. The simulation results show that the technique is highly convergent with superior performance operating for different payloads.
Keywords: Stewart kinematics, Stewart dynamics, task space control, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18935022 Passenger Seat Vibration Control of Quarter Car System with MR Shock Absorber
Authors: Devdutt, M. L. Aggarwal
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Semi-active Fuzzy control of quarter car system having three degrees of freedom and assembled with magneto-rheological (MR) shock absorber is studied in present paper. First, experimental work was performed on an MR shock absorber under different excitation conditions to obtain force-displacement and force-velocity curves. Then, for the application of experimental data in semi-active quarter car system, a polynomial model was selected. Finally, Fuzzy logic controller was designed having the combination of Forward fuzzy controller and Inverse fuzzy controller for integration in secondary suspension system of concerned model. The proposed controlled quarter car model was compared with uncontrolled system using simulation work under bump type of road excitation. Results obtained by simulation work shows the effectiveness of fuzzy controlled suspension system in improving the ride comfort and safety of travelling passengers compared to uncontrolled suspension system.
Keywords: MR shock absorber, three degrees of freedom, quarter car model, fuzzy controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32965021 Predictive Fuzzy Logic Controller for Agile Micro-Satellite
Authors: A. Bellar, M.K. Fellah, A.M. Si Mohammed, M. Bensaada, L. Boukhris
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This paper presents the use of the predictive fuzzy logic controller (PFLC) applied to attitude control system for agile micro-satellite. In order to reduce the effect of unpredictable time delays and large uncertainties, the algorithm employs predictive control to predict the attitude of the satellite. Comparison of the PFLC and conventional fuzzy logic controller (FLC) is presented to evaluate the performance of the control system during attitude maneuver. The two proposed models have been analyzed with the same level of noise and external disturbances. Simulation results demonstrated the feasibility and advantages of the PFLC on the attitude determination and control system (ADCS) of agile satellite.
Keywords: Agile micro-satellite, Attitude control, fuzzy logic, predictive control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17615020 Adaptive Neural Network Control of Autonomous Underwater Vehicles
Authors: Ahmad Forouzantabar, Babak Gholami, Mohammad Azadi
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An adaptive neural network controller for autonomous underwater vehicles (AUVs) is presented in this paper. The AUV model is highly nonlinear because of many factors, such as hydrodynamic drag, damping, and lift forces, Coriolis and centripetal forces, gravity and buoyancy forces, as well as forces from thruster. In this regards, a nonlinear neural network is used to approximate the nonlinear uncertainties of AUV dynamics, thus overcoming some limitations of conventional controllers and ensure good performance. The uniform ultimate boundedness of AUV tracking errors and the stability of the proposed control system are guaranteed based on Lyapunov theory. Numerical simulation studies for motion control of an AUV are performed to demonstrate the effectiveness of the proposed controller.Keywords: Autonomous Underwater Vehicle (AUV), Neural Network Controller, Composite Adaptation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25295019 Flexible Arm Manipulator Control for Industrial Tasks
Authors: Mircea Ivanescu, Nirvana Popescu, Decebal Popescu, Dorin Popescu
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This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.
Keywords: Distributed model, flexible manipulator, observer, robot control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16955018 Multi-objective Optimization with Fuzzy Based Ranking for TCSC Supplementary Controller to Improve Rotor Angle and Voltage Stability
Authors: S. Panda, S. C. Swain, A. K. Baliarsingh, A. K. Mohanty, C. Ardil
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Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.
Keywords: Multi-objective optimisation, thyristor controlled series compensator, power system stability, genetic algorithm, pareto solution set, fuzzy ranking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19375017 Comparison of Conventional Control and Robust Control on Double-Pipe Heat Exchanger
Authors: Hanan Rizk
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Heat exchanger is a device used to mix liquids having different temperatures. In this case, the temperature control becomes a critical objective. This research work presents the temperature control of the double-pipe heat exchanger (multi-input multi-output (MIMO) system), which is modeled as first-order coupled hyperbolic partial differential equations (PDEs), using conventional and advanced control techniques, and develops appropriate robust control strategy to meet stability requirements and performance objectives. We designed the proportional–integral–derivative (PID) controller and H-infinity controller for a heat exchanger (HE) system. Frequency characteristics of sensitivity functions and open-loop and closed-loop time responses are simulated using MATLAB software and the stability of the system is analyzed using Kalman's test. The simulation results have demonstrated that the H-infinity controller is more efficient than PID in terms of robustness and performance.
Keywords: heat exchanger, multi-input multi-output system, MATLAB simulation, partial differential equations, PID controller, robust control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 695