Sistem ve Kontrol Mühendisliği

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3D cow identification in cattle farms
(Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2013., 2015.) Arslan, Ahmet Cumhur.; Akar, Mehmet.
Animal farms have been steadily growing to meet the consumption requirements of the society in an e cient manner. This fact necessitates new monitoring and tracking systems to collect useful information about the herds in order to observe their general health and instantaneous state. However, recognizing and tracking an animal in a farm is a di cult task due to the target's similarity and hard to predict dynamics. In this thesis, a novel cow identi cation system is proposed. There are prominent features of this solution which di erentiates it from the others in the literature, i.e., it does not need any markers or external devices placed on the animal; works in even unlighted environments; identi es even black cows without distinctive coat patterns; is relatively cheaper, and enables accurate positioning. Proposed solution is based on 3D shape analysis of the top back part of the animals captured with RGBD cameras placed at an adequate height, where two dimensional images are constructed with respect to the local surface features and are subsequently identi ed by using face recognition methods. To evaluate the applicability of the proposed system, a real-time prototype software has been developed and a 3D cattle dataset is acquired which, to our knowledge, is unique in the literature. This dataset is gathered from moving animals which do not have distinctive coat patterns and captured in di erent lighting conditions. Applicability of the proposed solution has been veri ed by testing with the acquired dataset. Convincing results are obtained where %88 of 50 cows are identi ed successfully.
3D stylus: an intuitive 3D pointer for volumetric radiological data
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2007., 2007.) Yağcı, Enver.; Acar, Burak.
This work introduces a new human-computer interface(HCI) device for three dimensional (3D) visualized data. Although there are different approaches developed in the literature, 3D interfaces have not finished their development. The HCI we designed basically aims at taking an arbitrary cross-section (oblique slicing) from volumetric data. Additionally, the interface we called "3D Stylus" has an extra option which enables the user to draw two dimensional curves. The 3D Stylus is a colorful, long and thin structure like a pen. The 3D Stylus is tracked by using image processing algorithms. 3D information about the interface is acquired with the help of stereo processing techniques applied to the images come from the stereo camera. The 3D Stylus is a flexible tool that can be used for different purposes in different applications. In the thesis, we firstly develop a oblique slicing application using 3D Stylus as normal vector of slicer held by the user. Then another application is developed for 2D drawing, and the 3D Stylus used as a chalk. At the end of the thesis, experiments are presented. Users are asked to use the 3D Stylus and mouse interfaces in our applications. Results about efficiency of the 3D Stylus are given, compared with mouse.
A bayesian approach to textile defect detection problem and a comparative analysis
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2010., 2010.) Yakın, Abdullah.; Ertüzün, Ayşın.
The purpose of this thesis was to detect the defects on textile fabric images using the particle filters. We approached the problem from a Bayesian perspective and represented the model in a state space formulation. To describe the state space formulation; the texture models such as linear, 2-D linear and Markov Random Field models and the noise types like Gaussian, mixture of Gaussian and alpha-stable noise are investigated to find the best representation that is appropriate for our textile images. The implementation results are compared with Kalman, Extended Kalman and Unscented Kalman filters. Finally time and performance analysis of the filters is given.
A control framework for mobile payment systems
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2007., 2007.) Elçi, Kemal.; Şıkoğlu, Tamer.
Mobile payment on wireless devices will provide excellent business opportunities in the coming years and offers consumers convenience and flexibility of mobile services anytime and at any place, and is playing an increasingly important role in payments and banking. This prediction is supported when considering the high rate of penetration of mobile devices, especially mobile phones, PDA’s and other. Also an additional aspect is that the mobile phone can be used as payment device for all types of payment situations. Creating secure and cost-effective wireless payment solutions to support mobile device users not only provides good business opportunities, but also brings new technical challenges and issues to engineers. So how to build secured, easily manageable, wireless payment systems to support mobile payment transactions becomes a hot research topic. In this project, a stable, secure and reliable mobile payment system is designed and implemented. With rule-based, user-customizable fraud detection system and additionally implemented high level security precautions; user friendly and intuitive interface, this architecture offers a feasible mobile payment framework.
A fuzzy support vector machine approach for ECG analysis
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2010., 2010.) Özcan, N. Özlem.; Gürgen, Fikret.
In this thesis, fuzzy approach is used for ECG analysis. The ECG dataset in the UCI database is used. This dataset consists of inputs from normal and abnormal ECGs. All the anomalies are used to construct one class and normal ECG data is used to construct another class. The main purpose of the system is to detect anomalies correctly. In order to achieve this goal, a fuzzy support vector machine is constructed. Five different fuzzy membership functions are tested to reach the best performance: OCW, DTCM, DTOCM, CAR and FCM. Output of the fuzzy support vector machine system is compared to other classification methods. Results show that the fuzzy support vector machine outperforms other methods. In order to interpret the classification model, rule base extraction methods are applied. C4.5, PART, RIPPER and ANFIS are the selected algorithms for ECG rule base generation. When accuracy is considered as performance metric, RIPPER method outperforms the other techniques. The advantage of using ANFIS is the membership function generation for the features in the dataset. The resulting membership functions are found to be consistent with medical knowledge.
A Java based development environment for SpringFramework
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2008., 2008.) Kasap, Fatih.; Darcan, Osman Nuri.
Web application development is one of the most important programming areas today. There are many technologies to provide a better and easier way of programming for web applications in the market. Some of them are open source and free whereas some of them are released by big software vendors such as Microsoft and IBM. The SpringFramework is an open source alternative in this area. It is a Java-based technology to provide a robust infrastructure to software development based on best practices and accepted standards. This thesis aims to provide a computer program to facilitate SpringFramework-based web application development by hiding low level tasks from the developer and trying to make it focus on the real purpose of his application. Based on user friendliness and being close to human nature this program provides automatic code and web page generation, database and internationalization support, easy file management.
A model-free fractional-order PID tuning method based on an improvement of particle swarm optimization
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2010., 2010.) Seviş, Deniz.; Denizhan, Yağmur.
In recent times, applications of Fractional Calculus have gained importance in various areas of science and engineering. In the realm of control engineering Fractional Calculus started to draw the attention of researchers a decade ago with its most common application, namely Fractional-Order PID control, in contrast to its integerorder counterpart, it provides more flexibility in PID controller design applications with having integral and derivative actions of arbitrary order. However, classical PID tuning methods become inapplicable. The closed-loop system behavior exhibits sensitivity especially depending on the order of the derivative action. This behavior leads to use derivative-free stochastic optimization techniques rather than deterministic search methods. The trend of biologically-inspired computational approaches brought forth many heuristic optimization techniques. Among the most popular ones one can count evolutionary algorithms and swarm algorithms. Given an assessable objective function to be optimized, PSO technique can be used as a model-free optimization method that belongs to the "blind search" category. The innovation in this study is an improvement in this technique that combines the "blind search" inherent to PSO with "knowledge- supported search" in cases where some systematic knowledge about the optimization problem is available. This study proposes a model-free fractional-order PID controller tuning method which is Knowledge-Supported Particle Swarm Optimization (PSO) technique, sug- gesting a different combination of classical PID tuning approaches and stochastic optimization approaches. The stochastic method will be based on the socalled Particle Swarm Optimization (PSO) Technique, which is becoming a popular design method ever since it was introduced. In this study Knowledge-Supported Particle Swarm Op- timization (PSO) technique is used for fractional-order PID controller tuning based on the design specifications maximum percentage overshoot, rise-time, settling-time, and steady-state value. Constructed objective function for optimization which yields a possible solution to the design problem is optimized using popular Particle Swarm Optimization and systematic knowledge about PID controllers. With the help of examples the superiority of the proposed method to classical PSO algorithm is presented.
A reinforcement learning based controller to minimize forces on the crutches of a lower-limb exoskeleton
(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2022., 2022) Utku, Aydın Emre.; Samur, Evren.; Öncü, Sinan.
The majority of the metabolic energy consumption of a lower-limb exoskeleton user comes from the upper body effort, since the lower body can be considered to be passive. However, the upper body effort of lower limb exoskeleton users is ignored during motion controller development process in the literature. In this thesis study, deep reinforcement learning is used to develop a locomotion controller that minimizes the ground reaction forces (GRF) on crutches. The rationale for minimizing the ground reaction forces is to minimize the upper body effort of the user. A model of the human-exoskeleton system with crutches is created in URDF and XML formats. Reward functions that encourage the forward displacement of the center of mass of the exoskeleton-human system without falling and extreme joint torques are shaped. The state-of-the-art methods, Twin Delayed Deep Deterministic Policy Gradient (TD3) and Proximal Policy Optimization (PPO), are employed with the RaiSim and MuJoCo physics simulators and with different algorithm specific parameters in multiple training trials. The employed networks generate the joint torques based on the joint angle and velocities along with the ground reaction forces on feet and crutch tips. These generated joint torques are directly sent to the exoskeleton model and a new state is observed after implementing the action that the deep RL framework provides. Policies trained by the TD3 and PPO methods on RaiSim are observed to fail to generate proper control commands for a stable and natural looking gait. In general, it is observed that the PPO method generated higher rewards than the TD3 method on RaiSim. After failing to develop a desired policy with RaiSim, MuJoCo is employed as the simulator. Eventually, a policy that can generate a reasonable gait with a desired crutch usage and with 35% minimization in GRFs with respect to the baseline policy is developed.
A space subdivision framework for virtual reality and haptic applications
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2006., 2006.) Diktaş, Engin Deniz.; Şahiner, Ali Vahit.
This thesis presents a framework based on spatial subdivision of triangular mesh objects with octrees for virtual reality and haptic applications. For efficient generation of octree representations a method based on Minkowski sums is developed. The calculation of Minkowski sums is achieved geometrically by direct manipulation of planes in 3D-space. For the evaluation of proximity queries a new data structure called the proximity octree is introduced. A technique for tracking of geometric features of convex objects that are in close proximity to a specific point of interest is developed and tested for a number of applications including haptic interaction.
Accessibility on the Web through semantic and social renarrations
(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021., 2021.) Hoş, Emre.; Denizhan, Yağmur.; Üsküdarlı, Suzan.
The Web was proposed in 1989 with the vision of being an open platform that everyone can access. This vision of providing accessibility to all people is one of the primary goals of the Web. To this end, the (WAI) was launched by W3C in 1997 mainly to improve the accessibility of Web for the people facing physical accessibility barriers. While such work is crucial, it falls short in delivering true accessibility, since further barriers to understanding the information exist. Such barriers are associated with the ability of a person to understand the information that reaches them, such as language, literacy, culture, and expertise. To overcome such barriers, this work utilizes the renarration method, the process of forming an alternative version for a pre-existing web document to reach alternative audience. Accordingly, this work proposes an ontology that represents renarrations, web documents, and social interactions of renarrators and renarrations, and interconnections between them to support creation of an ontology driven social renarration platform. A prototype that utilizes Solid, a web decentralization project, has been created to demonstrate the feasibility of the social renarration approach and the suitability of the ontology for supporting the realization of a decentralized social renarration platform that protects the provenance and privacy.
Adaptive fuzzy sliding mode control of a washing machine oscillating system
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2005., 2005.) Tamyaman, Can.; Kaynak, Okyay,
To prevent any mechanical damage, washing machines distribute the load (the laundry)before performing any spins. After some distributive motor movements, there may still besome load that does not lay homogenously on the surface of the tumble. This load may cause undesired oscillations of the system. In cases when the load is not distributedhomogenously, the washing machine senses this unbalanced distribution if it is over athreshold value and reduces the spin speed or does not perform the final spin in thewashing profile. Because the machine is allowed to perform the final spin if the unbalanced distribution measurements are under a certain limit; some undesired oscillations andovershoots in the displacement of the oscillating system of the washing machine is likely totake place. This shortens the mechanical life of the machine. Furthermore, any undesiredmovements of the machine may pose a danger in a household. For these reasons the risk of machine displacement should be calculated and tested on every washing machine at thedesign phase. The machines are either produced with a calculated risk of displacement, orthe spin profile is modified to reduce the risk according to the results of the tests at designlevel. In this thesis, the control of a washing machine suspension system is achieved byusing adaptive fuzzy sliding mode control methods. The design and implementations are carried out in MATLAB Simulink environment. In the thesis, first, the methods that aregoing to be used and their advantages are given. Then, the unbalanced distribution of loadand its effects on washing machines are explained. Finally, the behavior of the proposed suspension system is examined in Simulink environment.
Adaptive routing algorithm for vehicular networks in city environment
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2011., 2011.) Özsahakyan, B. Loran.; Alagöz, Fatih.
The most known position based routing protocol for high mobile vehicular ad-hoc networks is the Greedy Perimeter Stateless Routing (GPSR) protocol. This protocol contains two routing modes, the greedy mode and the recovery mode, and creates a neighbor list to make a routing decision. The GPSR uses the greedy forwarding method whereas hops that follow are chosen based on nodes which are geographically closer to the destination node among the neighboring nodes. Nevertheless, forwarding fails if the current node is geographically the closest but unable to forward the packets to the destination. In this situation, the GPSR algorithm acts in recovery (perimeter) mode which is the repair strategy of this algorithm. Some enhancements such as the Greedy Perimeter Coordinator Routing (GPCR) and the Greedy Border Superiority Routing (GBSR) have been proposed. In this thesis, a routing protocol which works on real city maps and takes into account the actual movements of vehicles in city environment is recommended. We describe Adaptive Routing Algorithm For Vehicular Networks (ARAV) as a solution that improves the packet delivery ratio of GPSR and also improves the GPCR with road vehicle density information. ARAV differs from GPCR and GBSR, in that it uses routing algorithms adaptively in two routing modes. In ARAV greedy mode, we address the shortcomings of GPCR by considering the density of the paths. Packets are routed from one junction to another, the direction and position of hops are determined by taking the density of the paths into consideration. Our simulation results show that the proposed ARAV protocol outperforms the GPSR protocol in terms of packet delivery, throughput, delay in one successful transmission and greedy/perimeter ratio.
Application of a prototype parallel processing computer for a recurrent neural network model
(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 1992., 1992.) Paksoy, Bekir Alper.; Cılız, Kemal.
In this study, Hopfield's binary neural network model is simulated using a software package simulating a bit serial single instruction multiple data (SIMD) mesh array processor, called the Blitzen massively parallel processor (BMPP). First, the parallel algorithms required for the simulation are designed. Then, the parallel implementation of the Hopfield network model has been formulated using these algorithms. The parallel implementation has been analyzed for the speed and the processor utilization. To do this, time complexity of the parallel implementation is derived and compared with the time complexity of a sequential algorithm. Finally, simulation results are analyzed and compared with the analytical derivations. The parallel algorithm described in this study for the simulation of the Hogfield network model on the BMPP architecture achieves a maximum speedup in the order of the square root of the number of processors employed. It is also shown that, for the same algorithm, the maximum possible speedup can be achieved only at a finite number of processors, and the processor utilization decreases as the number of processors is increased.
Application of variable structure systems theory for training of intelligent systems
(Thesis (M.S.) - Bogazici University. Institue for Graduate Studies in Science and Engineering, 2001., 2001.) Yıldıran, Uğur.; Kaynak, Okyay,
Soft computing architectures with their extensive flexibility and strong mapping capabilities have been widely used for control of nonlinear systems. In this regard, error backpropogation and its derivatives have been the most popular and frequently employed schemes for parameter adjustment of these architectures. However, these schemes bring some serious problems together, like instability of closed loop system and sensitivity to uncertainties, which must be carefully addressed by a system designer. In order to alleviate these problems, recently, Efe has proposed a control strategy in which parameters of intelligent controllers are updated by a continuous-time robust parameters adjustment mechanism in order to robustify and stabilize the closed loop system dynamics. The results obtained for a two link SCARA robot in this study show that the proposed method is successful in achieving the control objectives. In this thesis, the methodology proposed by Efe is investigated for first order nonlinear systems. Based on the results, it has been observed that the time evolution of input-output curves of different structures show similar characteristics. Moreover, a modification is proposed for update mechanism of all architectures in order to prevent unbounded parameter evolution problem which occurs in the original algorithm. Lastly, based on the results for different systems, it has been concluded that the Adaptive Linear Element is the most suitable architecture for the control systems investigated because of its simplicity.
Assessment of technology development activities in turkish technoparks
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2007., 2007.) Polat, Çağlar.; Yıldırım, Ramazan,
In this study, a survey was conducted among the firms in Turkish technoparks in order to asses the technology development activities in these technoparks. A questionnaire was prepared and distributed to the firms in five technoparks in three cities in face to face interview. These technoparks are İTÜ ARI Technocity in stanbul, TÜBİTAK MAM Technocity in Gebze, Kocaeli, GOSB Technopark in Gebze, Kocaeli, Cyberpark (Bilkent University) in Ankara, and ODTÜ Technocity in Ankara. The questionnaire was distributed to 242 corporations in these technoparks, and it was filled by 168 companies. It was found that the majority of the firms are in the software related businesses and originated by the industry (85.7 percent) rather than the university. Apparently most of the firms are developing their own product or service although patent application is not quite common. This is also evident from the relatively high R&D spending (53 percent of budget) and the ratio of the employees working in R&D (73 percent). The university graduates constitute the highest percents in both R&D (46.1 percent) and other fields (17.4 percent). Various reasons from tax privilege to R&D environment and supports were stated as the reasons to operate in a technoparks; and the technology development support mainly come from various institutes such as TÜBİTAK, TİDEB, TTGV and KOSGEB. The majority of the respondents believe that the technopark applications in Turkey are successful with respect to both the firms (73.7 percent of respondents) and the country (65.3 percent) while about 80 percent of the respondents consider the current status of Turkish technoparks in the world as “poor”. The benefits of the technoparks for the companies and the country, and the necessary conditions for the success were also asked and evaluated in terms of their importance and their realization level.
Authorship recognition in online social platforms
(Thesis (M.A.) - Bogazici University. Institute for Graduate Studies in the Social Sciences, 2017., 2017.) Kuzu, Rıdvan Salih.; Salah, Albert Ali.
Biometrics is the identi cation of a person by personal properties and traits, and can be divided into physiological based and behavioural based methods. In this thesis we investigate the identi cation of users of a social platform from their verbal behaviour, which is an example of behaviour based biometrics. Online social platforms implement moderation mechanisms to lter out unwanted content and to take action against possible cases of verbal aggression and abuse, sexual harassment, and such. Since they can have large numbers of users, it is desirable to automatize parts of this process. What we call chat biometrics aims to re-identify a user from chat messages. The typical application scenario is the re-identi cation of banned users, returning under di erent identities, and aggressors operating through multiple fake accounts. We propose a processing pipeline, and contrast the problem with the authorship identi- cation problem, which is well-studied in the literature. We evaluate our proposed approach on a large corpus of multiparty chat records in Turkish (namely, the COPA database), which was collected from a multiplayer game environment. We also introduce a new corpus in this study, collected from a well-known Turkish social platform called Ek sisozluk, in order to test the robustness of the system across domain changes, as well as on Portuguese and English news datasets, to show performance across languages. We evaluate both pro le-based and instance-based approaches, and provide detailed analyses with regards to the required amount of text to identify a person reliably.
Automated requirements classification using feature selection based on linguistic features
(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021., 2021.) Çevikol, Sercan.; Aydemir, Fatma Başak.
Requirements classification is an important problem in organizing the systems and requirements, and it is widely used in handling large requirements data sets. A basic example of a requirements classification problem is the distinction between the functional and non-functional (quality) requirements. The state-of-the-art classifiers are most effective when they use a large set of word features such as text n-grams or part of speech n-grams. However, as the number of features increases, it becomes more difficult to interpret the approach, because many redundant features have to be explored that do not capture the meaning of the requirements. In this study, we propose the use of more general linguistic features, such as dependency types, for the construction of interpretable machine learning classifiers for requirements engineering. Through a feature engineering effort, assisted by tools that interpret graphically how classifiers work, we derive a set of linguistic features. While classifiers that use the proposed features fit the training set slightly worse than those that use high-dimensional feature sets, this approach performs generally better on validation data sets and is more interpretable. We use industry data sets, and we perform experimental runs using several automated feature selection algorithms to explore whether our feature set can be optimized further using one of the automated selection algorithms. Although in some data sets, impressive results were obtained. the automated selection algorithms did not prove a significant improvement, and even, on average, the results were worse than the results we obtained using the set based on linguistic features.
Classification and detection of wheezes in respiratory sounds
(Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2020., 2020.) Şerbetçi, Çağlayan.; Kahya, Yasemin.; Şen, İpek.
Analyzing respiratory sounds and detecting anomalies in them with intelligent computer algorithms has opened a new era for auscultation that has 250 years of history. These algorithms can overcome the drawbacks of conventional stethoscopes and support medics about auscultation. In this thesis, a new intelligent algorithm to detect wheezes superimposed on vesicular sounds is developed and presented. Detection of wheezes with intelligent algorithms is one of the hot topics currently being researched by many researchers. They are continuous musical adventitious respiratory sounds. Their duration, intensity, and phase in respiratory sounds give essential information for the diagnosis and prognosis of respiratory diseases. In this study, one of the aims is to determine the best discriminative features among nine features which are mostly used in other researches. The other aim is to find the best-performed machine learning classifier to classify wheezes and normal respiratory sounds. Last, we created a novel detection algorithm is presented to detect correctly the wheeze interval in recorded respiratory sounds by employing selected machine learning model to respiratory sounds.
Comparison of path planning algorithms
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2007., 2007.) Geleri, Fuat.; Akın, H. Levent.
Path planning problems arise in many different fields such as; robotics, assembly analysis virtula prototyping, pharmaceutical drug design, manufacturing, and computer animation. Path planning algorithms aim to solve problems that involve computing a continuous sequence, a path, of configurations between an initial and goal configuration. Planning of a path involves some constraints, such as computing a collision-free path. We compared various path palnning and navigation algorithms. as reactive algorithm, an improved version of Artificial Potential Field (APF) algorithm is used. In robot coordination this algorithm is the superior algorithm. It coordinates 250 robots easily. whereas deliberative algorithms, such as Rapidly-exploring Random Tree Connect (RRT Connect) algorithm, can only coordinate 40 robots with high costs. The other deliberative algorithms, Rapidly-exploring Random Tree (RRT), Probebilistic Roadmap (PRM) and Lazy Probabilistic Roadmap (Lazy PRM), could not coordinate more than 20 robots within feasible resource and time limits in our tests. In robot coordination reactive algorithms are more succesful, but, when the environment contains local minima, using a deliberative algorithm iv inevitable. In path palnning for multiple robots, decentralized approaches, or partially grouping of the robots show better performances. As the number of the controlled robots in the environmental increases, using decentralized approaches becomes a requirement, because the amount of the required time and the resources increases exponentially in centralized approaches, but linearly in decentralized approaches. partially grouping of the robots gives the best performance results, because the resource requirements increase nearly linear, and nearby robots are controlled in centralized manner
Control of inverted pendulum:| comparison of various strategies for swing up and balancing
(Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2005., 2005.) Er, Fatih.; Istefanopulos, Yorgo.
In this thesis, two different control schemes are designed for swinging up and three different schemes for balancing of an inverted pendulum, a non-linear electro-mechanical system with open loop unstablity. The controllers which are implemented for experimental purpose are a heuristic control technique using fuzzy logic and an energy control technique for swinging up. In order to balance the pendulum in the upright equilibrium, state feedback control, LQR control which is an optimal control technique and well known traditional control technique PID control are implemented. The control objective is swinging up the pendulum from its initial downward equilibrium to the upward and then balance at this state while it is tracking of desired trajectory. Three different combinations of proposed control schemes are chosen and their performances are compared with each other. Having compared all combinations, it is observed that every controller has advantages and merits for different cases.

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