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In this work a new optimization method, called the heuristic Kalman algorithm (HKA), is presented. This new algorithm is proposed as an alternative approach for solving continuous , non-convex optimization problems. The principle of HKA is to explicitly consider the optimization problem as a measurement process designed to give an estimate of the optimum. A(More)
The main objective of this paper is to present a new optimization approach, which we call heuristic Kalman algorithm (HKA). We propose it as a viable approach for solving continuous nonconvex optimization problems. The principle of the proposed approach is to consider explicitly the optimization problem as a measurement process designed to produce an(More)
H ∞ control Robustness Non-convex optimization problems Heuristic Kalman algorithm a b s t r a c t This paper presents a simple but effective tuning strategy for robust PID controllers satisfying multiple H ∞ performance criteria. Finding such a controller is known to be computationally intractable via the conventional techniques. This is mainly due to the(More)
one can see Eq. (3) is not very simple but it is used a few times for each image and so computing time are not signiicantly changed. Another problem is that now epipolar lines are no more parallel; anyway, if theta is small, one can suppose them to be still parallel and so performing the matching in the way seen before. All of this leads to a decay in(More)
The aim of this paper is to present a classifier based on a fuzzy inference system. For this classifier, we propose a parameterization method which is not necessarily based on an iterative training. This approach can be seen as a pre-parameterization which allows the determination of the rules base and the parameters of the membership functions. We also(More)