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"Control of linear parameter varying systems compiles state-of-the-art contributions on novel analytical and computational methods for addressing system identification, model reduction, performance analysis and feedback control design and addresses address theoretical developments, novel computational approaches and illustrative applications to various fields. Part I discusses modeling and system identification of linear parameter varying systems, part II covers the importance of analysis and control design when working with linear parameter varying systems (LPVS) , Finally, part III presents an applications based approach to linear parameter varying systems, including modeling of a turbocharged diesel engines, Multivariable control of wind turbines, modeling and control of aircraft engines, control of an autonomous underwater vehicles and analysis and synthesis of re-entry vehicles."

"Pencarian solusi pada sistem persamaan non-linier dapat dilakukan dengan cara langsung maupun tidak langsung. Salah satu cara tidak langsung yang digunakan adalah metode numerik. Metode Newton merupakan salah satu metode numerik untuk mencari solusi pada sistem persamaan non-linier. Metode Newton-like merupakan improvisasi dari Metode Newton, yang memiliki sebuah parameter berupa bilangan real yang berperan sebagai pengontrol kecepatan konvergensinya. Metode ini bersifat konvergen kuadratik, serta dianggap lebih baik daripada metode Newton untuk matriks Jacobi yang mendekati singular pada vektor inisial. Simulasi numerik dilakukan pada Metode Newton dan Newton-like dengan menggunakan lima sistem persamaan non-linier, yang masing-masingnya menggunakan empat nilai real untuk parameter pada Newton-like. Vektor inisial didapat dengan membuat nilai determinan Matriks Jacobi pada sistem persamaan non-linier mendekati nol. Berdasarkan simulasi numerik yang telah dilakukan, metode Newton-like secara umum lebih cepat konvergen daripada metode Newton. Kemudian, dari masing-masing sistem dapat ditentukan ada atau tidaknya sebuah nilai parameter optimal pada Metode Newton-like.

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Finding solutions on systems of non linear equations can be done by direct or indirect way. One of the inderect way is numerical methods. Newton method is one of the numerical methods to find solutions on systems of non linear equations. Newton like is an improvement of Newton method, which has a real parameter as the convergence speed regulator. This method is quadratic convergent, and considered better than Newton for Jacobian that is close to singular on initial vector.

Numerical simulations are performed on Newton and Newton like using five systems of non linear equations, which each system using four real values for the parameter on Newton like. The initial vector is obtained by making the determinant of Jacobian on systems close to zero. Newton like are generally faster than Newton Method. Later, from each system can be determined whether or not an optimal value on Newton like Method. "

"In this book, which focuses on the use of iterative methods for solving large sparse systems of linear equations, templates are introduced to meet the needs of both the traditional user and the high-performance specialist. Templates, a description of a general algorithm rather than the executable object or source code more commonly found in a conventional software library, offer whatever degree of customization the user may desire. Templates offer three distinct advantages: they are general and reusable; they are not language specific; and they exploit the expertise of both the numerical analyst, who creates a template reflecting in-depth knowledge of a specific numerical technique, and the computational scientist, who then provides "value-added" capability to the general template description, customizing it for specific needs. For each template that is presented, the authors provide: a mathematical description of the flow of algorithm; discussion of convergence and stopping criteria to use in the iteration; suggestions for applying a method to special matrix types; advice for tuning the template; tips on parallel implementations; and hints as to when and why a method is useful."