A novel moving horizon control strategy for input-saturated nonlinear polynomial systems is proposed. The control strategy makes use of the so called sum-of-squares (SOS) decomposition, i.e. a convexification procedure able to give sufficient conditions on the positiveness of polynomials. The complexity of SOS-based numerical methods is polynomial in the problem size and, as a consequence, comp...

In many mixed integer programs there is some embedded problem structure which can be exploited, often by a decomposition. When the relaxation in each node of a branch-andbound tree is solved by column generation, one speaks of branch-and-price. Optionally, cutting planes can be added in order to strengthen the relaxation, and this is called branchprice-and-cut. We introduce the common concepts ...

The paper addresses the fault detection (FD) problem for a class of discrete-time Markov jump linear systems (MJLSs) with deficient transition rates, which simultaneously considers the totally known, partly unknown, and uncertain transition rates. Then, in accordance with the linear matrix inequality (LMI) method and the convexification techniques, a sufficient condition for the existence of FD...

We have a set S ⊂ {0,1}n, together with, for each x ∈ S, the result of some unknown function F : {0,1}n → {0,1} applied to x, and a method for generating a hypothesis h ∈ H about F given S. We present theoretical and experimental results on four possible methods (similarity, convexification, prevalence and Hamming distance) for determing, given two elements y,z ∈ {0,1}n\S, whether we should be ...

We present a novel human body gesture recognition method using a linear programming based matching scheme. Instead of attempting to segment an object from the background, we develop a novel successive convexification linear programming method to locate the target by searching for the best matching region based on a graph template. The linear programming based matching scheme generates relativel...

The aim of this note is to demonstrate that Kaplansky–Hilbert lattices and injective Banach lattices may be produced from each other by means of the well known convexification procedure. This is done via the Boolean valued analysis approach. The subject gives a good opportunity to discuss also the relationship between the Kantorovich’s heuristic principle and the Boolean value transfer principl...

In the paper, a recurrent neural network based on an augmented Lagrangian function is proposed for seeking local minima of nonconvex optimization problems with inequality constraints. First, each equilibrium point of the neural network corresponds to a Karush-KuhnTucker (KKT) point of the problem. Second, by appropriately choosing a control parameter, the neural network is asymptotically stable...

We propose the moment cone relaxation for a class of polynomial optimization problems (POPs) to extend the results on the completely positive cone programming relaxation for the quadratic optimization (QOP) model by Arima, Kim and Kojima. The moment cone relaxation is constructed to take advantage of sparsity of the POPs, so that efficient numerical methods can be developed in the future. We es...

Logical implications appear in a number of important mixed-integer nonlinear optimal control problems (MIOCPs). Mathematical optimization offers a variety of different formulations that are equivalent for boolean variables, but result in different relaxations. In this article we give an overview over a variety of different modeling approaches, including outer versus inner convexification, gener...

Consider a finite exchange economy first as a static, 1 period, economy and then as a repeated economy over T periods when the utility of each agent is the mean utility over T. A family of strategic games is defined via a set of six general properties the most distinct of which is the ability of agents to move commodities forward in time. Now consider Pareto optimal allocations in the T period ...