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In this paper, a finite-time trajectory tracking control approach is proposed for an unmanned surface vehicle (USV) with unknown dead-zones and unknown disturbances. External disturbances can be observed exactly by a robust homogeneous differentiator with finite-time convergence. Based on the information of the bounds of the dead-zone slopes as well as treating the time-varying inputs coefficients...
The convex combination of two momentum term based algorithms with different momentum factors is an effective solution to highlight the tradeoff between convergence rate and steady-state error of a blind source separation system. As the smoothing factor is chosen in the range from 0 to 1, however, the performance of this convex combination is restricted. In this paper, a novel variable smoothing factor...
To solve the premature convergence problem of particle swarm optimization, two novel methods are introduced to adjust the inertia weight in parallel according to different fitness values of two dynamic sub-swarms. When the fitness values of the particles are worse than the average, the inertia weight is adjusted by the introduced dynamic piecewise linear chaotic map which can make the local-optima...
To solve the premature convergence problem of particle swarm optimization, two novel methods are introduced to adjust the inertia weight in parallel according to different fitness values of two dynamic sub-swarms. When fitness values are better than or equal to the average, two types of dynamic nonlinear equations are proposed to adjust the inertia weight in a continuous convex area which can retain...
A no velocity particle swarm optimiser with forgetting factor and center is presented. In the algorithm, the position of a particle is influenced not only by the personal best position and global best position but also by the swarm's center , and a particle has only position without velocity similar to bare bones PSO. The proposed algorithm determined by four real parameters is theoretically analyzed...
The blind multi-channels identification problem is studied in this paper. A cost function based on the orthogonal property between the output autocorrelation matrix and the channels parameter matrix is first constructed for a signal-input multiple-output FIR system. Then, an improved particle swarm optimizer, in which the personal best particle is replaced with the weight average of personal best...
Blind decorrelation is a related task to blind source separation (BSS) which is applicable to numerous problems. A critical challenge in adaptive blind decorrelation (ABD) is the choice of step size to achieve fast initial convergence speed and low steady state error in time-varying systems. Unfortunately, unlike some supervised training, the error factor of ABD is inaccessible in practice, and so...
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