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The proposed SQP MPC strategy is then described in detail.
The sampling period of the entire algorithm (models adaptation, Kaiman filters update, SQP optimization) has been set to 0.
To use of the advantage of GSA and SQP methods, and at the same time to overcome the drawbacks of these methods, a hybridization of GSA with SQP is proposed in .
The SQP algorithm is a non-linear programming technique that is used for the purpose of minimizing a smooth nonlinear function subjected to a set of constraints with upper and lower bounds.
Table I compares the total daily operating costs when the BFA is used to minimize the total cost of the microgrid with the SQP and MADS considering the optimal settings for the four investigated cases.
Rather than create this SQP in a vacuum, the producibility engineer develops the control dimensions in conjunction with the casting engineer to ensure key characteristics are understood and controls are well designed into the casting process.
To find the global optimum parameters with the lowest cost and a good accuracy, the Kriging interpolation, described in the next section, is adopted and coupled with SQP algorithm.
A mathematical basis for a complete simulation-based SQP (CSB-SQP) methodology was developed and applied to a simple model arising in determining the optimal control for the operation of HVAC&R building systems (Sun and Reddy 2005).
California Polytechnic State University SQP, 11(3), ASQ.
An SQP optimization algorithm, implemented in a multi-objective optimization software, was used to determine the values of geometrical control parameters that minimize the fibres breakage.
These nonlinear engineering problems have been investigated by many researchers that used different methods to solve them: Branch and Bound using SQP , Recursive Quadratic Programming , Sequential Linearization Algorithm , Integer-discrete-continuous Nonlinear Programming , Nonlinear Mixed-discrete Programming , Simulated Annealing , Genetic Algorithms , Evolutionary Programming  and, Evolution Strategies  among many others.
We determined the muscle activations required to generate the moments calculated previously using an SQP optimization routine  such that the overall muscle stress was minimized.
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