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"Penelitian ini akan mengembangkan pengendali MIMO Model Predictive Control (MPC) dengan constraints serta ditambahkannya fungsi Laguerre. Metode ini akan diterapkan pada sistem tata udara presisi atau biasa disebut sistem Precision Air Conditioning (PAC) dengan dua masukan, yaitu putaran kipas dan kompresor, dan dua keluaran, yaitu temperatur dan kelembapan relatif. Permasalahan yang ada pada proses kendali PAC ini ialah tetap menjaga temperatur dan kelembaban dari suatu sistem refrigasi sesuai dengan yang hasil yang diinginkan, yaitu pada temperatur 20-25 oC dan kelembaban relatif 40-55%. Penelitian ini adalah pengembangan dari penelitian sebelumnya yang tidak bisa mengendalikan sistem PAC dengan hasil yang memuaskan. Metode identifikasi yang digunakan menggunakan metode PO-MOESP untuk mencari model A, B, C, D dan menjadi masukan pengendali prediktif. Fungsi Laguerre ditambahkan untuk mengurangi waktu komputasi ke dalam MPC. Penelitian ini menggunakan software Matlab untuk melakukan proses simulasinya. Hasil keluaran pengendali MPC constraints biasa akan dibandingkan dengan pengendali MPC constraints dengan fungsi Laguerre.

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This research will aim to develop MIMO Model Predictive Control (MPC) controller with constraints added with Laguerre function. This method will be applied to Precision Air Condition (PAC) system with two inputs : fan and compressor speed; and two outputs : temperature and humidity. The problem in this PAC control process is to maintain temperature and humidity of the refrigeration system as desired, which is temperature 20-25oC and relative humidity 40-55 %. This research is developed from previous research, which could not control PAC system with feasible result. System identification used in this research is PO-MOESP method to find A, B, C, D model as input for predictive controller process. Laguerre Function was added for reducing computation time into MPC Controller. This research use MatLab software to run the process simulation model. Output of the conventional MPC controller with constraints will be compared to MPC controller with constraints and Laguerre function."

"This volume comprises a collection of contributions by leading experts in system identification, time-series analysis, environmetric modelling and control system design."

"The book then presents its core material, which is a more robust maximum principle for both deterministic and stochastic systems. The results obtained have applications in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games. Using powerful new tools in optimal control theory, this book explores material that will be of great interest to post-graduate students, researchers, and practitioners in applied mathematics and engineering, particularly in the area of systems and control."

"ABSTRACTCampak (morbili atau measles) adalah penyakit sangat menular yang disebabkan oleh virus dalam keluarga Paramyxovirus melalui kontak langsung dan udara. Di Indonesia, sejak tahun 2014 hingga Juli 2018, Kementerian Kesehatan mencatat terdapat 57.056 kasus terduga campak dan rubella (campak Jerman), dengan 8.964 kasus di antaranya merupakan kasus positif campak. Pada skripsi ini dibahas mengenai model matematis yang digunakan untuk menggambarkan perilaku dari data insiden lapangan penyakit campak di DKI Jakarta. Pada model tersebut, estimasi parameter laju penularan penyakit campak dilakukan agar parameter dapat menggambarkan data insiden lapangan penyakit campak di DKI Jakarta. Pendekatan yang digunakan dalam estimasi parameter adalah teori kontrol optimal dengan metode langsung yang meminimumkan selisih antara hasil I simulasi dan I data insiden penyakit campak di DKI Jakarta. Simulasi dilakukan untuk membahas skenario yang mungkin dapat menghasilkan estimasi parameter β terbaik. Hasil simulasi numerik menunjukkan bahwa hasil estimasi parameter terbaik diperoleh jika menggunakan dengan 1 sebagai koefisien pemberat pada selisih antara hasil simulasi I dan data I. Hasil simulasi numerik juga menunjukkan bahwa hasil estimasi parameter hanya baik digunakan untuk menghampiri satu periode kejadian penyakit campak, tetapi kurang baik dalam memprediksi kejadian campak di masa mendatang.

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ABSTRACTMeasles is a highly contagious disease caused by a virus in the Paramyxovirus family through direct contact and air. In Indonesia, from 2014 to July 2018, Ministry of Health noted 57,056 cases of suspected measles and rubella, with 8,964 cases were positive cases of measles. In this thesis, a mathematical model explaining the behavior of incident data of measles in DKI Jakarta, is discussed. On the model, parameter of the rate of transmission of measles ( ) is estimated so the parameter could describe the behavior from incident data of measles in DKI Jakarta. The approach used is the optimal control theory with the direct method which minimizes the difference between the simulation results and the incident data in DKI Jakarta. Simulations are carried out to disscus which scenario that can provide the best parameter estimation. The numerical simulation results indicate that the estimated parameter is best generated if with 1 as the weight coefficient on the difference between the results of the I simulation and I data. Numerical simulation results also show that the results of parameter estimation are only good for approaching a period of measles incidence, but not good at predicting the incidence of measles in the future."

"This book gives a comprehensive treatment of the fundamental necessary and sufficient conditions for optimality for finite-dimensional, deterministic, optimal control problems. The emphasis is on the geometric aspects of the theory and on illustrating how these methods can be used to solve optimal control problems. It provides tools and techniques that go well beyond standard procedures and can be used to obtain a full understanding of the global structure of solutions for the underlying problem. The text includes a large number and variety of fully worked out examples that range from the classical problem of minimum surfaces of revolution to cancer treatment for novel therapy approaches. All these examples, in one way or the other, illustrate the power of geometric techniques and methods. "

"Distributed decision making and Control is a mathematical treatment of relevant problems in distributed control, decision and multiagent systems, The research reported was prompted by the recent rapid development in large-scale networked and embedded systems and communications. One of the main reasons for the growing complexity in such systems is the dynamics introduced by computation and communication delays. Reliability, predictability, and efficient utilization of processing power and network resources are central issues and the new theory and design methods presented here are needed to analyze and optimize the complex interactions that arise between controllers, plants and networks. The text also helps to meet requirements arising from industrial practice for a more systematic approach to the design of distributed control structures and corresponding information interfaces Theory for coordination of many different control units is closely related to economics and game theory network uses being dictated by congestion-based pricing of a given pathway. The text extends existing methods which represent pricing mechanisms as Lagrange multipliers to distributed optimization in a dynamic setting. In Distributed Decision Making and Control, the main theme is distributed decision making and control with contributions to a general theory and methodology for control of complex engineering systems in engineering, economics and logistics. This includes scalable methods and tools for modeling, analysis and control synthesis, as well as reliable implementations using networked embedded systems. "