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"Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting the authors."

"This book presents a comprehensive overview of the recently developed L1 adaptive control theory, including detailed proofs of the main results. The key feature of the L1 adaptive control theory is the decoupling of adaptation from robustness. The architectures of L1 adaptive control theory have guaranteed transient performance and robustness in the presence of fast adaptation, without enforcing persistent excitation, applying gain-scheduling, or resorting to high-gain feedback."

"Neural networks and fuzzy systems are model free control design approaches that represent an advantage over classical control when dealing with complicated nonlinear actuator dynamics. Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities brings neural networks and fuzzy logic together with dynamical control systems. Each chapter presents powerful control approaches for the design of intelligent controllers to compensate for actuator nonlinearities such as time delay, friction, deadzone, and backlash that can be found in all industrial motion systems, plus a thorough development, rigorous stability proofs, and simulation examples for each design. In the final chapter, the authors develop a framework to implement intelligent control schemes on actual systems. Rigorous stability proofs are further verified by computer simulations, and appendices contain the computer code needed to build intelligent controllers for real-time applications. Neural networks capture the parallel processing and learning capabilities of biological nervous systems, and fuzzy logic captures the decision-making capabilities of human linguistics and cognitive systems."

"Pengendali adaptif pada Pressure Process Rig Feedback 38-714 dengan mekanisme adaptasi, yaitu faktor pelupa lebih kecil dari 1, menunjukkan performa yang baik jika set-point yang diberikan cukup tereksitasi. Pada sistem dengan setpoint kurang tereksitasi, pengendalian adaptif dengan mekanisme adaptasi menghasilkan fenomena Bursting, yaitu fenomena di mana sistem tidak terkontrol akibat gagalnya kerja estimator. Untuk mengatasi hal tersebut dirancanglah suatu algoritma supervisi. Algoritma supervisi ini berfungsi untuk menata kinerja estimator dan sintesa pengendali dan untuk memastikan lup pegnendalian selalu stabil. Pada skripsi ini, algoritma supervisi memantau besaran sinyal rata-rata dan variansi kesalahan prediksi, autokorelasi sinyal kendali, variansi parameter model, dan letak kutub parameter model terestimasi. Besaran - besaran ini dihitung secara rekursif (setiap pencuplikan) dari besaran ? besaran yang dihasilkan oleh pengendali adaptif. Algoritma supervisi ini diaplikasikan pada pengendalian adaptif Pressure Process Rig (Feedback 38-714). Dari uji eksperimen terbukti bahwa pengendalian adaptif dengan supervise memberikan hasil pengendalian yang lebih baik dibandingkan dengan pengendalian adaptif tanpa supervisi.Hal tersebut dapat terlihat dari tidak adanya fenomena bursting yang terjadi pada pengendali adaptif dengan supervisi yang mempunyai mekanisme adaptasi dan set-point kurang tereksitasi.

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Adaptive controlling on Pressure Process Rig Feedback 38-714 with adaptation mechanism, that has forgetting factor less than 1, shows good performance if the set-point given excite enough. In the system with less excitation, adaptive control with adaptation mechanism results Bursting phenomenon, that is phenomenon where system can?t be controlled anymore because of the estimator failure. Supervision algorithm is designed to cope with that problem. This supervision algorithm rule is organizing estimator?s work and controller design to make sure that control closed-loop always stable.

In this bachelor thesis, supervision algorithm monitors some parameters, there are mean and variance of prediction error signal, autocorrelation of control signal, variance of model parameter, and place of estimated model poles. These parameters are recursive calculated (every sample time) from adaptive control parameter yielded. This supervision algorithm is implemented on Pressure Process Rig (Feedback 38-714) with adaptive control.

From experiment test, it is proved that adaptive control with supervision gives better control result than adaptive control without supervision. It can be seen from no Bursting phenomenon that happened in adaptive control with supervision level that has adaptation mechanism and less excitation set-point."

"Vehicle dynamics and control provides a comprehensive coverage of vehicle control systems and the dynamic models used in the development of these control systems. The control system applications covered in the book include cruise control, adaptive cruise control, ABS, automated lane keeping, automated highway systems, yaw stability control, engine control, passive, active and semi-active suspensions, tire-road friction coefficient estimation, rollover prevention, and hybrid electric vehicles. In developing the dynamic model for each application, an effort is made to both keep the model simple enough for control system design but at the same time rich enough to capture the essential features of the dynamics. A special effort has been made to explain the several different tire models commonly used in literature and to interpret them physically.In the second edition of the book, chapters on roll dynamics, rollover prevention and hybrid electric vehicles have been added, and the chapter on electronic stability control has been enhanced."

"This book discusses new techniques for detecting, controlling, and exploiting the impacts of temperature variations on nanoscale circuits and systems. A new sensor system is described that can determine the temperature dependence as well as the operating temperature to improve system reliability. A new method is presented to control a circuit’s temperature dependence by individually tuning pull-up and pull-down networks to their temperature-insensitive operating points. This method extends the range of supply voltages that can be made temperature-insensitive, achieving insensitivity at nominal voltage for the first time."

"Pengendali PD merupakan pengendali yang sudah teruji dan banyak diterapkan pada proses pengendalian suatu sistem, salah satu penerapannya yaitu pada pengendalian kemudi kapal kargo, Walaupun pengendali PD (fixed parameters) ini bekerja dengan baik ruunun peiformance-nya menurun pada saat kapal mengalami perubahan kecepatan maupun saat terjadinya gangguan seperti angin, ombak dan arus. Selain itu diperlukan waktu yang cukup lama dalam melakukan penalaan terbadap parameter-parameter pengendali PD jika proses penalaan itu dilakukan secara manual (trial and error). Oleh sebab itu dibutuhkan suatu metode untuk mengatasi permasalahan tersebut. Pada skripsi ini dibahas mengenai penerapan GMRAC (Genetic Madel Reference Adaptive Control) dalam proses pengendalian kemudi kapal kargo. GMRAC merupakan sistem kendali adaptif yang didalamnya terdapat algoritma genetika sebagai metode penalaan terhadap pengendali dari suatu plant (kendalian) yang berdasarkan acuan dari model referensi sistem tersebut. Algoritma genetika digunakan sebagai teknik pencarian parameter-parameter pengendali PD berdasarkan mekanisme genetika dan seleksi alam, sedangkan model referensi digunakan sebagai acuan agar hasil keluaran dari sistem yang dikendalikan berkelakuan sesuai dengan performance yang diinginkan. Proses penalaan pengendali PD dilakukan secara dinamis terhadap perubahan kecepatan kapal maupun saat adanya gangguan (disturbance) yang sangat mempengaruhi dinamika kapal kargo. Hasil pengendalian kemudi kapal kargo dengan GMRAC disimulasikan dengan menggunakan perangkat lunak MATLAB versi 5.3 yang ditampilkan berupa grafik tanggapan waktu untuk menunjukkan settling time, rise time, peak time, overshoot dan error steady state serta grafik error antara model referensi dan system GMRAC. Berdasarkan karakteristik tanggapan waktu dan grafik error tersebut akan dilihat performance dari pengendalian GMRAC terhadap perubahan kecepatan kapal maupun dalam mengatasi gangguan (disturbance) yang menerpa kapal."

"Advances in reconfigurable mechanisms and robots I provides a selection of key papers presented in the second ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots (ReMAR 2012) held on 9th -11th July 2012 in Tianjin, China. This ongoing series of conferences will be covered in this ongoing collection of books.A total of seventy-eight papers are divided into seven parts to cover the topology, kinematics and design of reconfigurable mechanisms with the reconfiguration theory, analysis and synthesis, and present the current research and development in the field of reconfigurable mechanisms including reconfigurable parallel mechanisms. In this aspect, the recent study and development of reconfigurable robots are further presented with the analysis and design and with their control and development. The bio-inspired mechanisms and subsequent reconfiguration are explored in the challenging fields of rehabilitation and minimally invasive surgery. Advances in Reconfigurable Mechanisms and Robots I further extends the study to deployable mechanisms and foldable devices and introduces applications of reconfigurable mechanisms and robots.The rich-content of Advances in Reconfigurable Mechanisms and Robots I brings together new developments in reconfigurable mechanisms and robots and presents a new horizon for future development in the field of reconfigurable mechanisms and robots."