This paper presents a continuous-time version of recent results on unconstrained nonlinear model predictive control (MPC) schemes. Based on a controllability assumption and a corresponding infinite-dimensional optimization problem, performance estimates and stability conditions are derived in terms of the prediction horizon and the sampling time of the MPC controller. Moreover, improved estimat...

In this note we consider the properties of the Hamming distance in combinatorial optimization problems on hypergraph matchings, also known as multidimensional assignment problems. It is shown that the Hamming distance between feasible solutions of hypergraph matching problems can be computed as an optimal value of linear assignment problem. For random hypergraph matching problems, an upper boun...

in the current work, different methods for optimization of turbine blade internal cooling are investigated, to achieve higher cyclic efficiency and output power for a typical gas turbine. a simple two-dimensional model of c3x blade is simulated and validated with available experimental data. the optimization process is performed on this model with two different methods. the first method is a po...

This paper suggests an optimization-based methodology for the design of minimum weight structures with kinematic nonlinear behavior. Attention is focused on three-dimensional reticulated structures idealized with beam elements under proportional static loadings. The algorithm used for optimization is based on a classical optimality criterion approach using an active-set strategy for extreme lim...

Optimization of specific power of axial flux permanent magnet brushless DC (PMBLDC) motor based on genetic algorithm optimization technique for an electric vehicle application is presented. Double rotor sandwiched stator topology of axial flux permanent magnet brushless DC motor is selected considering its best suitability in electric vehicle applications. Rating of electric motor is determined...

In this paper, a new algorithm which is the result of the combination of cellular learning automata and frog leap algorithm (SFLA) is proposed for optimization in continuous, static environments.At the proposed algorithm, each memeplex of frogs is placed in a cell of cellular learning automata. Learning automata in each cell acts as the brain of memeplex, and will determine the strategy of moti...

Investment casting is a versatile manufacturing process to produce high quality parts with high dimensional accuracy. The process begins with the manufacture of wax patterns. The dimensional accuracy of the model affects the quality of the finished part. The present study investigated the control and optimization of dimensional deviations in wax patterns. A mold for an H-shaped wax pattern was ...

in this paper, reduced order proper orthogonal decomposition method has been used for simulation of unsteady incompressible flow fields. after projection of the governing equations along pod modes, a low-dimensional dynamical system is achieved. normally, standard low-dimensional models, due to some reasons, do not predict time variations of flow field accurately. accuracy of dynamical system h...

In this paper, a new hybrid conjugate gradient algorithm is proposed for solving unconstrained optimization problems. This new method can generate sufficient descent directions unrelated to any line search. Moreover, the global convergence of the proposed method is proved under the Wolfe line search. Numerical experiments are also presented to show the efficiency of the proposed algorithm, espe...