Given a nonlinear system and a control law, a new method to obtain cutting planes excluding points not belonging to the maximal admissible invariant set is proposed. The method uses linearization along the trajectory ...
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Given a nonlinear system and a control law, a new method to obtain cutting planes excluding points not belonging to the maximal admissible invariant set is proposed. The method uses linearization along the trajectory of the close-loop system to obtain a set of cutting planes. The main advantage of the approach is that if an inner approximation of the maximal admissible invariant set is available, the provided cutting planes do not intersect this initial approximation. A scaled version of an initial invariant set is used to improve the cutting planes obtained by linearization. The proposed approach can be used in the context of nonlinear model predictive control. The method is illustrated by an example.
The present paper deals with fault tolerant control for linear dynamics with additive disturbances. The control action is generated based on information collected from a redundant, multi-sensors network. Delays that m...
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The SIFT algorithm had a profound impact on the area of image local feature extraction and computer vision, since its inception. Because of its robustness and anti-interference performance, it has been widely applied ...
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We present a method for the calculation of approximate explicit solutions to constrained time-optimal control problems for nonlinear discrete-time systems. We aim to pre-compute offline a low complexity control law th...
We present a method for the calculation of approximate explicit solutions to constrained time-optimal control problems for nonlinear discrete-time systems. We aim to pre-compute offline a low complexity control law that provides feasibility guarantees and fast online computation. Related approaches build on hyperrectangular state space partitions that, unfortunately, lead to a large number of regions. We introduce a method based on a hierarchy of Voronoi diagrams, which leads to partitions with fewer elements. Thereby, we use the aforementioned hyperrectangular partitions as initializations and try to systematically reduce the number of regions.
This paper proposes a supervisory control structure for networked systems with time-varying delays. The control structure, in which a supervisor triggers the most appropriate controller from a multi-controller unit, a...
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A Norm-Optimal Iterative Learning control (NOILC) solution is developed for the problem when tracking is only required at a subset of isolated time points along the trial duration. Well-defined convergence properties ...
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Differential Ant Stigmergy Algorithm (DASA) is a recent meta-heuristic method which represents an adaptation of Ant Colony Optimization (ACO) to continuous optimization problems. Other adaptations of ACO to continuous...
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Differential Ant Stigmergy Algorithm (DASA) is a recent meta-heuristic method which represents an adaptation of Ant Colony Optimization (ACO) to continuous optimization problems. Other adaptations of ACO to continuous optimization exist but DASA seems to be very efficient for the class of highdimension real-parameters optimization problems, becoming a competitor to more classical methods such as Particle Swarm Optimization (PSO). The PSO is a meta-heuristic which is also inspired from insects' life as ACO. Even both methods use a population of entities, the memory of PSO is larger as those of DASA. DASA uses just one current solution around which the population search and the difference that generated last improvement. PSO stores the previous best position and velocity of every particle. This paper attempts to examine if an elitist version of DASA has at least the same effectiveness (finding the true global solution) as PSO, but with significantly better efficiency (less function evaluation). The performance comparison of DASA and PSO is implemented using a set of six test functions well known for their difficulty.
In this work, we present two unconstrained MPC schemes using additional weighting terms which allow to obtain improved stability conditions. First, we consider unconstrained MPC with general terminal cost functions. I...
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ISBN:
(纸本)9781467320658
In this work, we present two unconstrained MPC schemes using additional weighting terms which allow to obtain improved stability conditions. First, we consider unconstrained MPC with general terminal cost functions. If the terminal cost is not a control Lyapunov function, but satisfies a relaxed condition, then our results yield improved estimates for a stabilizing prediction horizon. Furthermore, our analysis also allows to recover two well-known results as special cases: if the terminal cost function is chosen as zero, we recover previous conditions on the length of the prediction horizon such that stability is guaranteed; and if the terminal cost is a control Lyapunov function conform to the stage cost, stability follows independently of the length of the prediction horizon. Second, we propose to use an exponential weighting on the stage cost in order to improve the stability properties of the closed-loop. This also allows to consider local controllability assumptions in combination with a suitable terminal constraints and thereby gives a connection to the classical MPC approaches using terminal constraints.
When identifying a dynamic system the model order has to be determined unless it is a priori known. For an errors-in-variables situation where both input and output measurements are noise corrupted, this is a nontrivi...
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The efficiency of the solid-rotor induction machines depends on axial length of rotor (including the end-regions). Determination of the best axial length is problematic because of current density distribution in the e...
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The efficiency of the solid-rotor induction machines depends on axial length of rotor (including the end-regions). Determination of the best axial length is problematic because of current density distribution in the end-regions and also because of absence of dedicated methods and models. This work proposes a method that circumvents this difficulty. It is based on the numerical determination of a dimensionless rotor-end factor using a combination of three-and two-dimensional finite element models restricted to the motor rotor. Such the end factor can be used in both analytical and numerical model of the machine in order to determine the typical performance characteristics. In this work, using this method, we determined an optimal length of the slitted solid rotor of a motor operating at 12 000 rpm, that maximizes the motor efficiency. The results of computations and measurements, carried out on the laboratory test-stand, are presented.
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