This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obt...
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(纸本)1889335215
This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model.
The optimization problems of nonlinear model predictive control are generally non-convex and their convergence to global optima can hardly be assured. In mis paper, interval analysis is applied to such non-convex opti...
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Document Clustering is one of the popular techniques that can unveil inherent structure in the underlying data. Two successful models of unsupervised neural networks, Self-Organizing Map (SOM) and Adaptive Resonance T...
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The problem of either elimination or extraction of an unknown number of nonstationary complex sinusoidal signals burried in noise is considered. We derive a class of adaptive notch filtering algorithms which can be ef...
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This paper proposes the software package SISCON, dedicated to the evaluation of optimal decisions for large scale systems. SISCON firstly evaluates mathematical models developed from experimental data using LS methods...
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The problem of identification/tracking of quasi-periodically varying systems is considered. This problem is a generalization, to the system case, of a classical signal processing task of either elimination or extracti...
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The paper presents the requirements of measurement system for electric arc furnace parameters measurement and for working characteristic calculating. On this basis measurement signals were specified and measurement al...
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The optimization problems of nonlinear model predictive control are generally non-convex and their convergence to global optima can hardly be assured. In this paper, interval analysis is applied to such non-convex opt...
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The optimization problems of nonlinear model predictive control are generally non-convex and their convergence to global optima can hardly be assured. In this paper, interval analysis is applied to such non-convex optimization problems by taking advantage of its guaranteed numerical nature of global optimization and constraint satisfaction. Simulation result demonstrates the feasibility of applying interval analysis to discrete-time nonlinear model predictive control.
Software cybernetics explores the interplay between software and control and is motivated by the fundamental question whether or not and how software behavior can be controlled. In this paper, we formulate the underly...
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The problem of either elimination or extraction of an unknown number of nonstationary complex sinusoidal signals burried in noise is considered. We derive a class of adaptive notch filtering algorithms which can be ef...
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The problem of either elimination or extraction of an unknown number of nonstationary complex sinusoidal signals burried in noise is considered. We derive a class of adaptive notch filtering algorithms which can be efficiently (almost transientless) started, or restarted, using the results of local nonparametric, periodogram-based signal analysis.
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