Industrial Control Engineering

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Adaptive Control of Multi-layer Switched Reluctance Motor
(Addis Ababa University, 2018-12) Alem, Gebreziher; Mengesha, Mamo (PhD)
The multi-layer switched reluctance motor (MSRM) are receiving significant attention from industries because of its simple structure, inexpensive manufacturability and reliability. In addition multi-layer switched reluctance motor receiving renewed attention as a viable candidate for various adjustable speed and high torque applications such as in the automotive, traction and aerospace industries. Simple power electronic drive circuit and fault tolerance of converter are specific advantages of multi-layer switched reluctance motor drives, but excessive torque ripple has limited its use to special applications. It is well known that controlling the current adequately can minimize the torque ripple because current is directly proportional to torque. The magnetization characteristics of the SRM is highly non-linear making the flux linkage and torque as the non-linear functions of both the current and rotor position. Establishing this high precision nonlinear mapping between current and rotor position is used to control the motor accurately for the analysis and control of any switched reluctance motor system. The generating or motoring mode of operation of the motor depends greatly on the value of rising or falling torque and hence it needs to be controlling more accurately the torque ripples for the practical applications. This thesis investigates the use of fuzzy logic controller and a hybrid intelligent system which is adaptive neuro fuzzy inference system (ANFIS) to reduce the torque ripples of multi-layer switched reluctance motors. Matlab simulink models of multi-layer switched reluctance motors with fuzzy logic controller and adaptive neuro fuzzy inference system (ANFIS) are developed to carry out simulation studies under loaded conditions. A comparison results shows that with fuzzy logic controller, the torque ripple is reduced by twenty two percent (22%) as compared to that without any controller. It is further observed that the adaptive neuro fuzzy inference system (ANFIS) controller reduces the torque ripples by twenty six percent (26%) as compared to that without any controller. This clearly shows that the torque ripple is reduced by using fuzzy logic controller as well the adaptive neuro fuzzy inference system (ANFIS). Moreover, performance of the adaptive neuro fuzzy inference system is better because it includes learning mechanism to adapt itself to new dynamic conditions. Key words: Multi-layer switched reluctance motor, fuzzy logic controller, adaptive neuro fuzzy inference system, torque ripples
Adaptive Radial Basis Function Neural Network Based Hierarchical Sliding Mode Controller for 2-Dimensional Double Pendulum Overhead Crane
(Addis Ababa University, 2024-01) Wosene Yirga; Dereje Shiferaw (PhD)
Several control methods for an overhead crane modeled as a double pendulum with constant cable length have been published in various studies. Most of the proposed control methods were open-loop and linear control methods or nonlinear control methods that fully depended on the system model.However, the dynamic of an overhead crane is a complex nonlinear function of uncertain or unknown parameters, which reduces the performance of such control methods. In this thesis, an adaptive radial basis function neural network-based hierarchical sliding mode controller (ARBFNNHSMC) is designed to control a 2-dimensional overhead modeled as a double pendulum system with variable cable length using the Lagrange equation of motion. To reduce the chattering effect of the sliding mode controller as well as increase its robustness, ARBFNN is designed to estimate unknown or uncertain nonlinear functions in the system. The overall control law, which contains only some parts of the crane model, is designed, and the adaptation law is derived from the Lyapunov stability condition to update the weight of the network based on observed errors. The proposed control strategy and derived model are verified using MATLAB/Simulink software.For the same controller parameters,500% changes in model parameters are taken, and trolley displacement settling time and rising time for HSMC are 12.3 seconds and 6.95 seconds, respectively. On the other hand, the maximum hook’s and payload’s swing angles are around 1.34 deg and 1.9 deg for HSMC, and it is around 1.04 deg and 1.64 deg for ARBFNN-HSMC. The residual hook’s and payload’s swing angles are 0.0137 deg and -0.0319 deg, respectively, in the case of HSMC and -0.0011 deg and -0.0022 deg for ARBFNN-HSMC. This numerical result shows that ARBFNN-HSMC has better performance than HSMC for large parameter variations. In addition, the controller output of ARBFNN-HSMC is smoother than that of HSMC, as evidenced by the result.
Adaptive Super Twisting Sliding Mode Controller Design of Quadcopter for Wheat Disease Detection
(Addis Ababa University, 2023-11) Nardos Belay; Lebsework Negash (PhD)
Brown wheat rust is a fungal disease that can cause huge destruction in wheat production and quality. Collecting accurate large scale crop data and detecting these diseases based on certain standards through visual inspection is labor intensive, time consuming, and prone to human error. This paper focuses on the design of adaptive super twisting sliding mode controller of a quadcopter for detection of brown wheat rust disease. First, the dynamics of the system was understood then the Newton-quaternion approach was used to model the dynamic system and verified in simulink. Then, the adaptive super twisting sliding mode controller was developed for attitude and position trajectory tracking of a quadrotor. Controller design involves tuning the parameters of the supertwising sliding mode controller using adaptation laws. Comparison of conventional sliding mode controller with the adaptive super twisting sliding mode controller was analyzed. The effectiveness of the proposed control scheme has been verified by developing simulation results for quadcopter in MATLAB/SIMULINK software. The results show high tracking accuracy, chattering reduction, and disturbance rejection capability of the proposed controller. For the task of brown wheat rust detection, transfer learning technique was applied using the state of the art ResNet152v2 model to perform feature extraction for the convolutional neural network architecture. The trained model achieved an accuracy level of 93.28% in the training phase and 92% in the test set.
Adoption of Electric Vehicle and Efficiency Improvement of Storage System in Addis Ababa
(Addis Ababa University, 2021-10) Benyam, Girma; Mengesha, Mamo (PhD)
This thesis contributes to the problem description of the impact of geographical landscape and road dynamics in the process of adoption of electric vehicles in the case of Addis Ababa/Ethiopia. The impact of Addis Ababa road dynamics and topographic distribution of the city have been investigated and it was compared with various international drive cycles like EUDC, NYDC, and WLTP. By considering the worst possible scenario for modelling electric vehicle dynamics and energy storage system; this thesis provides an alternative engineering solution using battery and ultra capacitors. The investigation was done concerning electric vehicle regenerative braking energy gain possibilities and the magnitude of energy consumption from an energy storage system. From the simulation result, it was found that the magnitude of the maximum acceleration-deceleration was about 1.57m/s² and 2.81m/s² respectively and the frequency of stop time was around 31 with in the city. In addition to that, because of rugged nature of the topography; the tractive and regenerative energy consumption of the city was about 6637KJ and -281KJ respectively. It was observed that a larger magnitude of acceleration-deceleration rate and regeneration braking energy has been recorded compared to any other international city. Due to this nature of the city, 8 % state of charge battery variation has been found within 400 seconds of simulation time. From the finding, due to the nature of the city; battery Energy storage system is less efficient when compared to hybrid energy storage system hence electric vehicle implemented in the city of Addis Ababa/Ethiopia need to be redesigned. This thesis recommends fuzzy logic control based battery and ultra capacitor hybrid energy storage system which consider topographic distribution and road dynamics of the city. Adopting electric vehicles without considering the above issue may lead to performing under the manufacturer's specification. Specifically, degradation of batteries and reduced use of the range of travel per single charge.
AI-Based Mobile Robot for Agricultural Application using Sliding Mode Controller
(Addis Ababa University, 2023-05) Zewdu Jemema; Dereje Shiferaw (PhD)
Recent advancements in agricultural robotic systems have greatly enhanced their functionality, usability, and integration into various tasks, particularly in the field of agriculture. The primary goal of designing agricultural robots is to enhance efficiency, save time, and decrease production costs by incorporating controllers, sensors, actuators, and communication systems. These robots have versatile applications and are widely embraced in the agricultural sector in industrialized countries. Extensive research has been dedicated to developing mobile robot platforms tailored for agricultural tasks, including plant health monitoring, pesticide spraying, fruit picking, and harvesting, with the aim of supporting farmers in developing nations like Ethiopia, where approximately 67% of the population is involved in agriculture. The thesis specifically targets fruit harvesting and focuses on the challenging task of modeling, designing, and simulating a mobile manipulator with advanced capabilities for agricultural businesses, making it one of the most difficult undertakings in this field. The study encompasses the presentation of the mobile manipulator’s 3D design, kinematics, and dynamics. In addition, AI techniques are employed to analyze fruit images, facilitating the accurate detection and determination of fruits. Based on the results, the effectiveness of the training technique has been assessed using an RMSE value of 0.19 and a loss value of 3.6e-02. An SMC utilizes the input generated from the image to govern the mobile manipulator’s position. The system’s stability and robustness have been assessed by considering uncertainties and variations in mass. When comparing the performance of a designed controller with a PID controller in the presence of uncertainty and parameter variation, it was found that SMC outperformed. According to the evaluation using the ITAE, SMC proves to be more effective, demonstrating a 75% improvement compared to the PID controller. Overall, this research contributes to the development of a robust and intelligent mobile manipulator for fruit harvesting in the agricultural sector, with potential applications to support farmers in countries like Ethiopia.
Analysis and DSP Implementation of Sensor-less Direct FOC of Three-Phase Induction Motor Using Open-Loop Speed Estimator
(Addis Ababa University, 2017-05) Hambissa, Teshome; Mamo, Mengesha (PhD)
This thesis work deals with sensor-less speed control of induction motor in its entire speed range. Flux linkage and rotor speed estimators are designed, simulated and implemented on 180W induction motor using Texas Instrument DSP board TMDSHVMTRPFCKIT. Estimated flux-linkage has been used as reference for direct field oriented control of the machine currents and voltages. MATLAB software is used for design simulation of the estimators while Texas Instruments TMS320F2803x, power module with space vector modulation, inverter and code composer studio for software development, is used for practical experimentation. PI controller was used for both speed and current controller. The simulation and experimental result demonstrated good dynamic and steady state performance 3.38% overshoot and 31.4 rad/sec bandwidth have been achieved with 0.00375 steady state error
Analysis and DSP Implementation of Sensorless Speed Control of Induction Motor Using Model Reference Adaptive Controller and Luenberger Observer
(Addis Ababa University, 2020-06-10) Dita, Tilahun; Mengesha, Mamo (PhD)
In this thesis, a model reference adaptive system (MRAS) and Luenberger observer (LO) based speed estimator is designed to control the speed of induction motor with no mechanical speed sensor. The proposed method involves two models, reference and adaptive model for the estimation of rotor ﬂuxes and speed. The identiﬁed rotor ﬂuxes from the Luenberger observer system (reference system) are used for the identiﬁcation of rotor angular speed in the adaptive model. Induction motor is highly sensitive to motor parameter variation at low and zero speed. To overcome this parameter mismatch stability analysis is carried out. So that feasible range of operation is well known. Model reference adaptive system (MRAS) and Luenberger observer (LO) based sensorless speed estimator was analyzed in terms of different reference input tracking capability, torque response quickness, low speed behavior, response of drive with speed reversal, sensitivity to motor parameter variation. The system gives good performance at low speed and both at no load and loaded condition. From the simulation results, the rotor speed is estimated with a steady state error of 0.4% and good transient response with rise time of 0.023 second and settling time of 0.05 second. Rotor ﬂux is estimated with 0.024 second rise time, 0.2% steady state error and settling time of 0.05 second. Stator ﬂux is estimated with 0.02 second rise time, 2% second steady state error, settling time of 0.03 second and 17% of maximum overshoot. The proposed sensorless vector control operation is veriﬁed by simulation on MATLAB/Simulink and closed loop demonstration using Texas Instruments HVMTRPFCKIT with TMS320 F28035 DSP piccolo control card on 180w induction motor. From the demonstration work the rotor speed of the motor with maximum steady state error of 0.1800537% has been achieved under no load condition.
Backstepping Fuzzy Sliding Mode Controller for Trajectory Tracking of Mobile Manipulator
(Addis Ababa University, 2024-04) Geta Menyechel; Dereje Shiferaw (PhD)
A Mobile Manipulator (MM) is essentially a robotic arm attached to a mobile platform, which could be designed for space, ground, aerial, or underwater environments. The mobile platform expands the reach of the manipulator, allowing it to access a larger workspace. This increased mobility enhances the ability to position the manipulator in various configurations, leading to more efficient task execution. Mobile Manipulators has complex system structure, highly coupling dynamics between mobile base and mounted manipulator arm, holonomic and nonholonomic kinematics constraints and highly nonlinear characters substantially increase the difficulty in designing a controller for the wheeled mobile manipulator. Designing a robust controller for mobile manipulator with the aim of simultaneous control of the velocity of the mobile platform and the motion of the end-effector is the aim of this thesis work. By employing the concepts of kinematic backstepping control and fuzzy sliding mode torque control, a two-step control approach is introduced for the nonholonomic mobile manipulator. In the first step, the kinematic velocity control is designed to ensure that all desired trajectories are achieved. In the second step, a fuzzy sliding mode torque controller, based on the dynamics of the mobile manipulator, is designed to ensure that the mobile platform’s velocity and the end-effector’s position converge to the reference trajectories generated in the first step. The proposed method stability is proved using Lyapunov theory, and its convergence is mathematically guaranteed. Comparision between BSMC and the proposed BFSMC is conducted in terms of tracking performance in the face of both disturbance and parameter variation and the proposed BFSMC has shown better performance in tracking the given trajectory by rejecting the external disturbances and tolerating the parametric uncertainties results in performance improvement of 31.6%. The effectiveness of the suggested control approach is confirmed through the creation of simulation outcomes using MATLAB/SIMULINK software.
Boiler Drum Water Level Control Using Fuzzy Sliding Mode Controller
(Addis Ababa University, 2022-08) Jemila Wudu; Dereje Shiferaw (PhD)
Boiling water to create steam is a crucial step in the process industries. An important part of this process boiler drum water level control. For a variety of reasons, it's crucial to keep the drum's water level at the proper level. When the water level is too high, the steam purification equipment floods, which allows water and contaminants to leak into the steam system. The effectiveness of the treatment and recirculation function is decreased by a too-low water level. It is typically challenging to control the drum water level of the boiler due to the system's significant disturbance (like steam disturbance), nonlinearity in mathematical modeling, strong coupling between input and output parameters, and multivariable features. To overcome this problem a sliding mode controller with fuzzy logic controller (FSMC) is proposed. Also PID and SMC applied to the system in contrast. Since the drum water level controller's task is to level the boiler drum at startup point which is 10 perunit and keep it there at steady steam load. The results prove that sliding mode controller with fuzzy leads to better performance in overshoot, settling time and chattering effect elimination than PID and SMC controller. There is no overshoot in FSMC or 0 overshoot, has quick settling time which is 41.9228sec and no chattering effect. However, sliding mode controller exhibit fast rise time which is 13.1080sec than PID and FSMC which is 30.9 and 15.1947sec respectively. Also exhibit high chattering effect. This conduct is improper for a mechanical force or other physical indication. Additionally, in this work it is proven that when the amount of steam mass flow rate disturbance increase, achieving desired trajectory using PID controller decrease. But a desired trajectory can be achieved using SMC and FSMC whenever the steam mass flow rate disturbance increases. The water level control system is verified and simulated using MATLAB software.
Comparative Analysis of PID and Fuzzy Logic Controller for Induction Motor Speed Control
(Addis Ababa University, 2019-10) Awole, Hussen; Dereje, Shiferaw (PhD)
Induction motor (IM) is the most rigid, and relatively less expensive machine but much difficult to control. The advent of field-oriented control (FOC) makes IM useful in variable speed drive applications. The concept of FOC is to separate the torque and flux producing current and then control the torque and flux separately. The advent of different control theory makes difficulty in the choice of an appropriate controller. In this thesis, a comparative analysis of fuzzy and PID control for IM speed control has been done. To solve this problem first an indirect field-oriented control (IFOC) method motor control is designed. In this design, the direct current �� is kept constant for a fast response. In addition, the motor is modeled using rotor flux and stator current as a state variable. This model is very important due to the presence of measurable quantity (stator current), and to mathematically quantify the alignment of rotor flux on the d-axis. Both PID and fuzzy control of IM has been verified using simulation on MATLAB/SIMULINK. The performance of both PID and FLC is analyzed in terms of reference tracking, load variation, parameter variation, low-speed tracking, and speed reversal. The PID controller results 0.3s settling time with 10% overshoot and the fuzzy controller 0.2s settling time with 0% overshoot.
Control of Grid Connected Micro Hydro Power System
(Addis Ababa University, 2020-01) Getachew, Nadew; Mengesha, Mamo (PhD)
For a grid connected micro hydropower (MHP) system, power electronics and phase locked loop was designed and simulated in this research. The grid interconnection of MHP improve the reliability of the grid and helps to decrease transmission and distribution losses. However, the synchronization with the utility grid is the main concern of the inverter control design because the grid frequency, phase and voltage need to be tracked. If the inverter output cannot meet the local grid connection criteria, the power will not be allowed to deliver. In this research, mathematical modeling of micro hydro power plant has been done. The full bridge three phase diode rectifier, boost converter, inverter and LC filter are designed to connect the power generated to the grid. Then, by injecting the grid voltage signal in to the PLL, the phase voltage frequency and phase angle has been tracked to synchronize phase, frequency and voltage of the generated power with different grid condition. It is observed from the simulation results that for ideal grid conditions the phase angle was tracked and relatively faster and also precisely. Also the system can easily track the phase when the frequency was changed from 50Hz to 55Hz or 45Hz. The only difference from the ideal case is that the PI-regulator now approaches 2π*5rad/s for 55 Hz and -2π*5rad/s for 45Hz instead of zero. Moreover, different non-ideal grid conditions were simulated and almost handled by the system.
Control of lower limb exoskeleton with simulated EMG signal
(Addis Ababa University, 2016-04) Aberra, Bethlehem; Mamo, Mengesha
An exoskeleton robot is a kind of a man-machine system which mostly uses combination of human intelligence and machine power. The structure of an exoskeleton robot consists of joints and links which correspond to the human body. This thesis presents a control system for exoskeletons that utilizes the simulated electrical signals from the muscles, EMG signals, as the main means of information transportation between the human and the exoskeleton. A support action is computed in accordance to the patient’s intention and is executed by the exoskeleton. The mathematical model of the exoskeleton system was based on the mathematical model of a permanent magnet DC servo motor whose parameters can be selected by either Using system identification techniques on a prototype built or by selecting an actuator based on the requirement of the load torque. A linear quadratic Gaussian (LQG) controller for the lower-limb exoskeleton is designed and implemented. Furthermore the robustness of the system to sensor noise and unmodelled system dynamics were analyzed. The effectiveness of the proposed system is tested through simulation studies using Simulink® software. The 3-D model of the system designed using solidworks® is interfaced with the Simulink® model via Simulink® simmechanics product. The proposed control strategy has shown satisfactory performances in terms robustness and gentleness. The knee joint is to track the ideal range of motion with an error of less than 5 % with the use of LQG controller. The control law is also found to be robust with respect to external disturbances. Key words: Lower limb exoskeleton, Electromyography (EMG), Modeling, linear quadratic Gaussian (LQG) controller.
Control of Quad Rotor Unmanned Aerial Vehicle (UAV) Using LQG Track controller
(Addis Ababa University, 2016-06) Negese, Bekele; Prasad Singh, Nagendra (Professor0
This thesis is focused towards the studies on Vertical Take-Off and landing (VTOL) Unmanned Aerial Vehicle (UAV) quad rotor control. The quad rotor is controlled by four BLDC motors which act in different directions to control the yaw angle, roll angle and pitch angle and z-axis position. The control action basically depends on the controlled voltages fed to the four motors. The dynamic modelling of quad rotor is discussed and the design of Linear Quadratic Gaussian (LQG) is presented. A simulator based on MATLAB/SIMULINK model of UAV quad rotor is developed to carry out simulation studies. The effectiveness of the proposed LQG control algorithm to control the hovering position and cruising position in the presence of disturbances such as plant noise and sensor noise is investigated through simulation studies on the simulator. The effectiveness of the proposed controller is tested with and without disturbance through simulation studies. The first test is observed from model verification of open loop response. It is observed from the open loop response that the altitude control is done through three conditions. This was done by controlling the four input controls through rotors frequencies which are compared with the hovering frequencies. Closed loop simulation studies are carried out with the proposed LQG controller. It is observed that the desired tracking is achieved almost within 9 seconds after giving the step input command signals. Similarly, it is observed that the hovering position is achieved almost within 8 seconds after giving the step input command signals. It is further observed that the quad rotor tracks the command signals almost after 10 seconds under the influence of disturbance of covariance value 0.9. It is further observed that the quad rotor attains the desired hovering position after 9 seconds under the influence of disturbance of covariance value 0.9. Key words: VTOL, UAV, LQG, LQR, Kalman Filter, Tracking control, Hovering position Stabilization
Cost Effective Frequency control of Micro Hydro Power Plant
(AAU, 2018-03) Hanna, Berhanu; Mengesha, Mamo (PhD)
Micro Hydro-Power Plants (MHPPs) are a reliable solution for supplying small power consumers in areas located far from the distribution grid. However controlling frequency of the generated power is one of the main problems in micro hydro power plants. This thesis presents a control structure that ensures the frequency regulation of an induction generator (IG). Induction generator is chosen over synchronous generator because it has an advantage with price, robustness, simpler starting and controlling mechanism. The main work of this thesis is to design a cost effective frequency controller for MHPP. For the control of the frequency, a fuzzy logic controller is used. The controller is modeled, designed and simulated to be simple, fast response fuzzy logic based frequency control system and lower cost. For lower cost, the fuzzy logic controller is realized using Field Programmable gate array rather than microcontrollers. The frequency controller controls frequency of the micro hydro-power plant nearly constant. When the flow of water is minimum, the controller is designed to prevent component from damage by initiating a shutdown. It is observed from the simulation results that the overshoot of the fuzzy controller for 75% load change and 0.2 m 3 /s flow rate is 2.74%, 3.04% and 3.46% and the settling times are 20.87, 27.65 and 39.82 seconds. Moreover, the comparison of fuzzy logic controller and PI controller is observed. The fuzzy logic controller has been coded, compiled and simulated in VHDL using ModelSimAltera. From simulation result, the system inferred maximum operating frequency is 5 MHz with a critical path of 199.3 ns.
Design and Analysis of Fuzzy Logic Based Controller for Flow and Level Control of Cane in Wangi Sugar Factory
(Addis Ababa University, 2018-06) Yohannes, Solomon; Dereje, Shiferaw (PhD)
In a sugar production, flow and the amount of cane fiber carried by cane carrier varies due to non-uniformity of cane supply. The continuous variation of cane fibers flow and the level of cane fiber in chute during the cane juice extraction inversely affect the cane juice extraction efficiency of mill. In this thesis we have developed algorithm for a three input fuzzy controller with an aim to maintain the cane level in chute and flow during cane juice extraction. The developed controller generates signal that required controlling cane carrier motor speed depending upon the value of cane level in chute, quantity of cane on rake carrier and flow rate. The three inputs fuzzy controller is developed and simulated for six cases by using fuzzy logic toolbox of MATLAB. The performance of the controller is compared in terms of disturbance rejection, transient and steady sate performance. It is observed from the simulation results that the average overshoot is 0%, rising time is 0.0817 seconds and the settling time is 0.274 seconds with the proposed fuzzy controller while overshoot is 7.62%, rise time is 0.0513 second and settling time is 0.16 seconds with PID controller. Moreover, the robustness and disturbance rejection of the controllers is checked by parameter variation like time constant, delay time & DC gain and giving disturbance signal after settling time respectively. It is further observed that the proposed controller has better disturbance rejection and more robust.
Design and Comparative Analysis of Genetic Algorithm Tuned Fractional and Integer Order PI Controllers with Adaptive Neuro fuzzy Controller for Speed Control of Indirect Vector Controlled Induction Motor
(Addis Ababa University, 2019-01) Girma, Kassa; Dereje, Shiferaw (PhD)
This thesis presents design and comparative analysis of fractional order PI controller, integer order PI controller and an adaptive neurofuzzy controller trained by input output data from fractional order PI controller for indirect vector controlled induction motor. The parameters of the two PI controllers were genetically optimized using square of error as a fitness function. The proposed neurofuzzy controller trained with input and output data of fractional order PI controller incorporates fuzzy logic algorithm with a multilayer artificial neural network structure using hybrid learning algorithm. This improves the performance of induction motor drive. The fractional order model of induction motor has been also investigated using simulation results and it was inferred that optimized model of induction motor is an integer order model. The performance of adaptive neurofuzzy inference system controller, was compared with fractional and integer order PI controllers using MATLAB simulation results with different operating conditions. It was observed from the simulation results that by using ANFIS, FOPI, and IOPI controllers, for the reference speed of 50 rad/sec, the percentage peak overshoots were 0.496%,13.068% and 15.698% respectively. Thus, ANFIS shows dramatic decrease in overshoot. Also the speed reaches its desired set value at 0.15 second in ANFIS controlled IM drive. These show the effectiveness of the designed neurofuzzy controller and the designed neurofuzzy controller tries to speed up the performance of IM drive. On the other hand, FOPI controller showed better performance than IOPI controller for IM drive, this is because of FOPI controller has one additional parameter for tuning which is integration order.
Design and Compare Adaptive Neuro-Fuzzy Inference System (Anfis) With Genetic Algorithm (Ga) Tunned Pi Controller for Speed Control Of Vector Controlled Induction Motor Drive
(Addis Ababa University, 2018-11) Daniel, Arega; Dereje, Shiferaw (PhD)
Nowadays, vector controlled induction motor drives with variable speed applications are widely used in order to achieve good dynamic performance and wide speed control. The conventional speed controllers for vector control of induction motor drive suffer from the problem of stability; besides, these controllers such as PI/PID controllers show either steady state error or sluggish response to the agitation in reference setting or during load perturbation. In this thesis a new method of controlling technique based on the combination of Artificial Neural Network (ANN) and fuzzy logic (FL) is proposed to improve the speed control of indirect vector controlled induction motor drive. Indirect vector controlled induction motor with genetic algorithm (GA) optimized PI controller is developed and is replaced with adaptive neuro-fuzzy controller (ANFIS) to overcome the problem of overshoot occurred in PI controller and to obtain quick steady state response and better speed control. The proposed technique is implemented using MATLAB/Simulink. In this thesis, the speed, torque and stator current responses with GA based PI controller and proposed adaptive neuro-fuzzy controller are compared and found that the proposed ANFIS based controller showed increased dynamic performance. The proposed adaptive neuro-fuzzy controller is better in overshot which is 0.475% and that of PI controller is 14.368%, raise time and settling time.
Design and Implementation of Direct Torque Control Drive of Three-Phase Induction Motor based on DSP
(Addis Ababa University, 2019-06) Tesfaye, Meberate; Mengesha, Mamo (PhD)
Direct torque control (DTC) technology is a superior, modern and a new type of AC machine drive control technology developed after vector control technology. In this Thesis, the Direct Torque Control (DTC) scheme for Induction Motor Drive using Space Vector Modulation (SVM) technique is studied. DTC provides excellent properties of regulation, even if without rotational speed feedback. The technology directly controls the instantaneous value of the electromagnetic torque and stator flux-linkage through the control of stator flux linkage and electromagnetic torque in the stationary coordinate system and has the advantages of rapid torque response, simple control structure, and easy digitalization. These quantities are estimated with only stator voltages, stator currents, and stator resistance. The induction motor has been modeled and simulated in the stationary d-q reference frame and its transient and steady-state characteristics are drawn. The MATLAB Simulink consists of an induction motor mathematical model, a two-level hysteresis comparator for stator flux control, a three-level hysteresis comparator for torque control, a switching table for voltage vector selection, stator flux position identifier, a three-phase voltage source inverter (VSI), flux and torque estimators. The hardware circuit is composed of in addition to the MATLAB Simulink component it has three-phase Induction machine, TMDSHVMTRPFCKIT with other necessary equipment. The switching table is employed for selecting the optimum inverter output voltage vectors so as to attain a fast torque response, low inverter switching frequency, and low harmonic losses in the code. The simulation of DTC schemes (Conventional DTC) has been carried out using MATLAB/SIMULINK and the results are discussed. From estimated speed of simulation result it has good transient and steady state performance with overshoot 1.531% and with approximated steady state error 0.0002. High Voltage Motor Control and PFC Development kit (TMDSHVMTRPFCKIT) with TMS320F28035 Control Card is programmed using code composer studio for hardware implementation of the DTC scheme and the results are discussed. steady state estimated stator flux module has fluxuation from the reference with an error of 2.8% maximum ripple.
Design and Implementation of Feedback Linearization based Adaptive Stabilizing Controller Coupled with Fuzzy Logic Swing-up for Pendulum on a Cart
(Addis Ababa University, 2019-11-19) Daniel, Abebe; Dereje, Shiferaw (PhD)
This thesis address an adaptive stabilizing controller for inverted pendulum on a cart based on feedback linearization coupled with an adaptive fuzzy logic based swing up controller. First feedback linearizing control signal is derived by decomposing the system into cart subsystem and pendulum subsystem. Then adaptive inverse control technique is applied to each feedback linearizing control signals. An adaptive inverse control method is used for compensation of unknown parameters of an inverted pendulum on a cart, while feedback linearization is used to cancel non-linearity in the system. The pendulum is driven from it's pendant position to inverted position using an adaptive fuzzy logic based swing up controller. When the pendulum reaches near it's inverted position, the stabilizing controller takes over the swing up controller. The MATLAB/SIMULINK simulation shows that the proposed controllers adapt to unknown mass of a cart between 0:1kg - 4kg and mass of a pendulum between 0:01kg - 4kg. The performance of the stabilizing controller on hardware experimentation under unknown mass of a cart and mass of a pendulum shows that the proposed controller is a solution to inverted pendulum stabilization problem.
Design And Simulation of Fuzzy Logy Based Frequency Controller for Standalone Micro Hydro Power Plant
(Addis Ababa University, 2017-05) Getnet, Yalemzerf; Mamo, Mengesha (PhD)
Despite a long history of micro hydropower in Ethiopia, locally manufactured low cost frequency controllers are not well developed and are not available off-the-shelf in local market. The frequencies of micro hydropower plants are controlled by electronic load controllers. Unfortunately, these governors have harmonic effect on the system, waste more amounts of water and energy during low power demand. In this thesis, simple, less cost and fast response fuzzy logic based frequency control system is modeled, designed and simulated. The frequency controller controls flow rate of water by acting on electric valves and keep the frequency of the micro hydropower system nearly constant. In addition to this when flow rate is minimum, the controller designed to prevent component from damage by isolating loads from the system. It is observed from the simulation results that the average overshoot for 35% load change is 0.9% and the settling time is 26.85 seconds. Moreover, even for 75% load change, overshoot is only 3.04% and the settling time is 27.65 seconds. It is further observed that energy wasted on the valve is always around zero at steady state conditions. In addition the proposed controller is less expensive, which cost 10-20 USD than ELC which cost 70-120 USD per kilo watt. Generally both the transient and steady state performances are improved with fuzzy controller and the controller works efficiently under all operating conditions. Therefore, this controller can play crucial role for low cost micro hydro power plant development in rural part of Ethiopia. Key Words: Micro Hydropower, Fuzzy Logic Controller, Rural Electrification

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