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"This book presents a new approach for the analysis of chaotic behavior in non-linear dynamical systems, in which output can be represented in quaternion parametrization. It offers a new family of methods for the analysis of chaos in the quaternion domain along with extensive numerical experiments performed on human motion data and artificial data. All methods and algorithms are designed to allow detection of deterministic chaos behavior in quaternion data representing the rotation of a body in 3D space. This book is an excellent reference for engineers, researchers, and postgraduate students conducting research on human gait analysis, healthcare informatics, dynamical systems with deterministic chaos or time series analysis."

"Differential equations are the basis for models of any physical systems that exhibit smooth change. This book combines much of the material found in a traditional course on ordinary differential equations with an introduction to the more modern theory of dynamical systems. Applications of this theory to physics, biology, chemistry, and engineering are shown through examples in such areas as population modeling, fluid dynamics, electronics, and mechanics.Differential Dynamical Systems begins with coverage of linear systems, including matrix algebra; the focus then shifts to foundational material on nonlinear differential equations, making heavy use of the contraction-mapping theorem. Subsequent chapters deal specifically with dynamical systems concepts low, stability, invariant manifolds, the phase plane, bifurcation, chaos, and Hamiltonian dynamics. Throughout the book, the author includes exercises to help students develop an analytical and geometrical understanding of dynamics. Many of the exercises and examples are based on applications and some involve computation; an appendix offers simple codes written in Maple, Mathematica, and MATLAB software to give students practice with computation applied to dynamical systems problems."

"This book gives a unified presentation in an abstract setting of the main theorems in bifurcation theory, as well as more recent and lesser known results. It covers both the local and global theory of one-parameter bifurcations for operators acting in infinite-dimensional Banach spaces, and shows how to apply the theory to problems involving partial differential equations. In addition to existence, qualitative properties such as stability and nodal structure of bifurcating solutions are treated in depth. "

"Inverse limits provide a powerful tool for constructing complicated spaces from simple ones. They also turn the study of a dynamical system consisting of a space and a self-map into a study of a (likely more complicated) space and a self-homeomorphism. In four chapters along with an appendix containing background material the authors develop the theory of inverse limits. The book begins with an introduction through inverse limits on [0,1] before moving to a general treatment of the subject. Special topics in continuum theory complete the book. Although it is not a book on dynamics, the influence of dynamics can be seen throughout; for instance, it includes studies of inverse limits with maps from families of maps that are of interest to dynamicists such as the logistic and the tent families."

"The book includes a theory for flow barriers and passability to boundaries in discontinuous dynamical systems that will completely change traditional concepts and ideas in the field of dynamical systems. Edge dynamics and switching complexity of flows in discontinuous dynamical systems are explored in the book and provide the mathematical basis for developing the attractive network channels in dynamical systems. The theory of bouncing flows to boundaries, edges and vertexes in discontinuous dynamical systems with multi-valued vector fields is described in the book as a “billiard” theory of dynamical system networks. The theory of dynamical system interactions in discontinued dynamical systems can be used as a general principle in dynamical system networks, which is applied to dynamical system synchronization.　"

"Sistem multi-agent adalah suatu sistem yang terdiri atas beberapa agen yang mampu melakukan interaksi satu sama lain untuk mencapai tujuan bersama. Salah satu permasalahan dalam sistem multi-agent adalah permasalahan konsensus untuk menyamakan keadaan seluruh agen dengan mengurangi perbedaan keadaan suatu agen dengan agen lainnya. Berbagai jenis protokol pengendali telah dikembangkan untuk membuat seluruh agen mencapai konsensus, tetapi sebagian besar pengendali masih menggunakan mekanisme time-triggered yang mengharuskan pengendali pada setiap agen untuk melakukan komputasi di setiap waktu cuplikan sehingga beban komputasi cukup tinggi. Penelitian ini membahas mengenai pengendali prediktif (MPC) terdistribusi untuk menyelesaikan permasalahan konsensus pada sistem multi-agent dengan mekanisme event-triggered. Permasalahan konsensus dapat diselesaikan dengan menggunakan pengendali prediktif terdistribusi yang bekerja dengan melakukan optimalisasi fungsi objektif. Untuk mengurangi beban komputasi, mekanisme event-triggered digunakan sehingga pengendali melakukan optimalisasi fungsi objektif hanya ketika kondisi trigger terpenuhi. Pada penelitian ini, pengendali prediktif dengan mekanisme event-triggered diujikan terhadap sistem dengan model agen linear vehicle dan nonholonomic mobile robot melalui simulasi. Hasil simulasi yang diperoleh menunjukkan performa yang baik dalam mencapai konsensus dengan total waktu komputasi yang lebih sedikit dibanding menggunakan mekanisme time-triggered.

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Multi-agent system is a system consisting of several agents who are able to interact with each other to achieve a common goal. One of the problems in a multi-agent system is the problem of consensus to equalize the state of all agents by reducing the differences of an agent with other agents. Various types of controlling protocols have been developed to make all agents reach consensus, but most controllers still use a time-triggered mechanism that requires controllers in each agent to do computation at each sampling time so that the computing load is high enough.

This study examines the distributed predictive controller (MPC) to solve consensus problems on multi-agent systems with event-triggered mechanisms. Consensus problem can be solved using a distributed predictive controller that works by optimizing objective functions. To reduce computational load, an event-triggered mechanism is used so that the controller performs objective function optimization only when the trigger conditions are met.

In this study, predictive controllers with event-triggered mechanisms were tested on systems with linear vehicle and nonholonomic mobile robot agents through simulation. The simulation results show good performance in reaching consensus with less computational time than using time-triggered mechanisms."

"Penerapan dan penelitian mengenai multi agent system (MAS) saat ini sedang cepat berkembang. Penggunaan pengendali Model Predictive Control (MPC) cukup populer digunakan untuk menyelesaikan permasalahan konsensus pada korvengensi dan stabilitas MAS. Namun pada MPC konvensional masih terdapat masalah, masalah optimasi yang harus diselesaikan secara periodik menyebabkan pemborosan sumber daya komputasi dan komunikasi antar agen. Oleh karena itu, mekanisme tambahan diperlukan agar masalah optimasi dapat diselesaikan secara aperiodik. Pada peneltian ini, mekanisme self triggered ditambahkan pada pengendali MPC, dan dirancang untuk menyelesaikan permasalahan formation pada MAS dengan model nonholonomic mobile robot. Penggunaan mekanisme ini memungkinkan komputasi MPC tidak perlu dilakukan secara terus menerus, tapi digunakan bila dibutuhkan. Pengendali yang dirancang dibentuk dengan mengkombinasikan antara teori graph sebagai topologi komunikasi antar agent, dengan algoritma MPC, dan ditambah dengan mekanisme self triggered untuk menentukan kondisi kapan MPC melakukan optimasi. Pengendali Prediktif atau MPC akan memprediksi sinyal kendali agent sepanjang horizon prediction. Beberapa simulasi dilakukan untuk menguji rancangan desain pengendali self-triggered MPC, kemudian diuji untuk menyelesaikan permsalahan formation, lama waktu komputasi dihitung dan dibandingkan dengan MPC konvensional. Hasil uji simulasi menunjukan bahwa mekanisme self triggered mampu mengurangi beban komunikasi dan beban komputasi pada pengendali MPC.

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Application and study of multi-agent systems are growing fast. Model Predictive Control (MPC) has been popularly used to solve consensus problem in corvengence and stability of multi agent system (MAS). But conventional MPC is still having probrems, optimization problems is solved periodically, which may lead to a waste of computation and communication resources between agents. Therefore, additional mechanism is needed so optimization problems can be solved aperiodically. In this study, a self triggered mechanism was added to the MPC controller, which was designed to solve the formation problem for MAS on nonholonomic mobile robot. A self triggered condition allows MPC computing not to be done periodically, but is used if needed.

The designed controller is build by combining graph theory as a communication topology beetwen agents, with the MPC algorithm, and added with a self triggered mechanism to determine the conditions when does the MPC solved optimization. Predictive controllers or MPC is used to predict control signals along the horizon prediction. Several simulation are conducted to test the self triggered MPC controller design, were then tested to solve the formation problem. The computation time is calculated and compared with conventional MPC. The simulation test results show that the self triggered mechanism is able to reduce the communication load and computational load on MPC controllers."

"Perkembangan industri sawit di Indonesia memberikan dampak pada aspek sosial, ekonomi, dan lingkungan. Namun, dampak industri sawit pada aspek sosial, dan ekonomi lebih dominan dibandingkan dengan dampak pada aspek lingkungan dalam artian sawit lebih memberikan manfaat positif untuk peningkatan kesejahteraan masyarakat dan pertumbuhan ekonomi dibandingkan untuk peningkatan luas tutupan hutan, penurunan konflik kepemilikan lahan, dan potensi penurunan emisi. Intervensi pemerintah dalam bentuk penetapan kebijakan diperlukan untuk menyeimbangkan dampak industri sawit pada aspek ekonomi, sosial dan lingkungan. Intervensi kebijakan pemerintah semestinya komprehensif dan akurat maka dari itu perlu dirumuskan ke dalam bentuk model kebijakan sawit pemerintah dengan memperhatikan aspek sosial, ekonomi, dan lingkungan secara berimbang dengan tujuan mewujudkan sawit yang berkelanjutan. Permodelan kebijakan pemerintah untuk mewujudkan sawit yang berkelanjutan dengan system dynamicsbertujuan untuk menganalisis dampak intervensi kebijakan pemerintah pada industri sawit yang selanjutnya memberikan dampak pada aspek sosial, ekonomi dan lingkungan. Berdasarkan hasil permodelan, intervensi kebijakan sawit pemerintah memberikan dampak positif pada aspek sosial, dan lingkungan dalam industri sawit namun memberikan dampak negatif pada aspek sosial, dan ekonomi. Selanjutnya, ditetapka intervensi kebijakan lanjutan (counter policy) pemerintah untuk meminimalisir dampak negatif intervensi kebijakan sawit pemerintah pada aspek sosial, dan ekonomi dalam industri sawit. Intervensi kebijakan lanjutan berhasil memberikan dampak positif pada aspek sosial, dan ekonomi dalam industri sawit yang sebelumnya mengalami penurunan akibat intervensi kebijakan sawit pemerintah. Permodelan kebijakan pemerintah untuk mewujudkan sawit yang berkelanjutan berhasil menganalisis dampak intervensi kebijakan sawit pemerintah dan kebijakan lanjutan pemerintah pada aspek sosial, ekonomi, dan lingkungan dalam industri sawit sehingga dapat mewujudkan sawit yang berkelanjutan.

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The development of the palm oil industry in Indonesia has had an impact on social, economic, and environmental aspects. However, the impact of the palm oil industry on social and economic aspects is more dominant than the impact on environmental aspects in the sense that oil palm provides more positive benefits for increasing people's welfare and economic growth compared to increasing the area of ??forest cover, reducing land ownership conflicts, and reducing potential emissions. Government intervention in the form of establishing policies is necessary to balance the impact of the palm oil industry on economic, social, and environmental aspects. Government policy interventions should be comprehensive and accurate, and therefore need to be formulated in the form of a government palm oil policy model that pays attention to social, economic, and environmental aspects in a balanced way with the goal of realizing sustainable palm oil. Modeling government policies to realize sustainable palm oil with a dynamic system aims to analyze the impact of government policy interventions on the palm oil industry which in turn has an impact on social, economic, and environmental aspects. Based on the modeling results, the government's palm oil policy intervention has a positive impact on social and environmental aspects in the palm oil industry but has a negative impact on social and economic aspects. Furthermore, the government's counter policy intervention was established to minimize the negative impact of the government's palm oil policy intervention on social and economic aspects in the palm oil industry. Follow-up policy interventions have succeeded in having a positive impact on the social and economic aspects of the palm oil industry, which previously experienced a decline due to the government's palm oil policy interventions. Modeling government policies to realize sustainable palm oil has succeeded in analyzing the impact of government palm oil policy interventions and government follow-up policies on social, economic, and environmental aspects in the palm oil industry so that sustainable palm oil can be realized"