Katalin M. Hangos – författare

Analysis and Control of Polynomial Dynamic Models with Biological Applications synthesizes three mathematical background areas (graphs, matrices and optimization) to solve problems in the biological sciences (in particular, dynamic analysis and controller design of QP and polynomial systems arising from predator-prey and biochemical models). The book puts a significant emphasis on applications, focusing on quasi-polynomial (QP, or generalized Lotka-Volterra) and kinetic systems (also called biochemical reaction networks or simply CRNs) since they are universal descriptors for smooth nonlinear systems and can represent all important dynamical phenomena that are present in biological (and also in general) dynamical systems.

Describes and illustrates the relationship between the dynamical, algebraic and structural features of the quasi-polynomial (QP) and kinetic models Shows the applicability of kinetic and QP representation in biological modeling and control through examples and case studies Emphasizes the importance and applicability of quantitative models in understanding and influencing natural phenomena

Analysis and Control of Polynomial Dynamic Models with Biological Applications synthesizes three mathematical background areas (graphs, matrices and optimization) to solve problems in the biological sciences (in particular, dynamic analysis and controller design of QP and polynomial systems arising from predator-prey and biochemical models). The book puts a significant emphasis on applications, focusing on quasi-polynomial (QP, or generalized Lotka-Volterra) and kinetic systems (also called biochemical reaction networks or simply CRNs) since they are universal descriptors for smooth nonlinear systems and can represent all important dynamical phenomena that are present in biological (and also in general) dynamical systems.- Describes and illustrates the relationship between the dynamical, algebraic and structural features of the quasi-polynomial (QP) and kinetic models- Shows the applicability of kinetic and QP representation in biological modeling and control through examples and case studies- Emphasizes the importance and applicability of quantitative models in understanding and influencing natural phenomena

Almost all process systems are nonlinear in nature. Nonlinear control is traditionally an area of interest in process systems engineering which is of great practical importance. These facts notwithstanding, many process engineers have difficulty with the paradigms and results of modern nonlinear control theory because they lack the mathematical background usually associated with such methods or because of their computational difficulty and small-scale applicability in the general case. Analysis and Control of Nonlinear Process Systems overcomes these barriers.Features:- The necessary mathematical preliminaries for readers from a process engineering background- Constant reference to the widely-known finite-dimensional linear time-invariant continuous case as a basis for extension to the nonlinear situation- The most promising theories and analytical methods for nonlinear process control laid out clearly and straightforwardly with exercises to reaffirm the techniques as they are taught- Emphasis on the importance of process knowledge and first-principles-based models in obtaining feasible and effective solutions in particular circumstances from general cases- Illustration of applications with simple examples and case studiesAnalysis and Control of Nonlinear Process Systems will interest graduate process engineers wishing to study advanced control methods either with a view to further research or application in industry as well as to academics seeking to move process control courses into more complicated but up-to-date territory. It will also be a great assistance to those in their senior undergraduate years who will form the next generation of industrial process engineers and need unfussy access to the most modern nonlinear control ideas.