Optimal control problem Pontryagin maximum principle

Lynn ei ai (1970) obtain the optimal temperature profiles for a tubular reactor with axial dispersion (Lynn et ai, 1970). Weighted residual techniques were used to solve the state and adjoint differential equations which result from the application of Pontryagin s maximum principle to the optimal control problem. 

One of the most profound results of applied mathematics, Pontryagin s minimum principle provides the necessary conditions for the minimum of an optimal control problem. The elegance of the principle lies in the simplicity of its application to a vast variety of optimal control problems. Boltyanskii et al. (1956) developed the principle originally as a maximum principle requiring the Hamiltonian to be maximized at the minimum. 

Depending on the numerical techniques available for solving optimal control or optimisation problems the model reformulation or development of simplified version of the original model was always the first step. In the Sixties and Seventies simplified models represented by a set of Ordinary Differential Equations (ODEs) were developed. The explicit Euler or Runge-Kutta methods (Huckaba and Danly, 1960 Domenech and Enjalbert, 1981) were used to integrate the model equations and the Pontryagin s Maximum Principle was used to obtain optimal operation policies (Coward, 1967 Robinson, 1969, 1970 etc.). 

Chapter 4 applies variational calculus to problems that include control variables as well as state variables. Optimal control strategies are developed that extremize precise performance criteria. Necessary conditions for optimization are shown to be conveniently expressed in terms of a mathematical function called the Hamiltonian. Pontryagin s maximum principle is developed for systems that have control constraints. Process applications of optimal control are presented. 

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