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A stabilizing regulator designed by any technique whatsoever can be viewed as the combination of a state estimate feedback controller and additional feedback from a dynamic compensator driven by the residual signal (difference between actual and estimated system outputs). Motivated by such an observation, this paper presents the controller design from the premise that system stability is first guaranteed...
This paper develops an effective multi-objective feature selection algorithm based on differential evolution (DE). In the algorithm, a randomized localization mutation based on Pareto domination is used to improve the convergence of DE. A self-adaptive crossover is proposed to dynamically assign the crossover probability of each individual. Based on it, the promising regions around good individuals...
Up to now, classical Quantum Particle Swarm Optimization Algorithm in the late period of convergence has showed some drawbacks, such as population diversity reduce, convergence speed slow down and easy to fall into local optimal solution. This paper improves the classic QPSO algorithm and proposes Grouped Quantum-inspired Particle Swarm Optimization (G-QPSO). In this algorithm, quantum particles are...
Optimization problems with more than three objectives, i.e., many-objective problems (MaOPs), have gained more and more attentions in the field of evolutionary multi-objective optimization (EMO) in that the powerful Pareto comparisons and evolutionary strategies are very scarce. Particle swarm optimization (PSO) is an effective method for multi-objective problems, however, it has not been well scaled...
Odor source localization is very important in real-world applications. We studied the problem of odor source localization and presented a modified particle swarm optimization algorithm for odor source localization of multi-robot. The algorithm dynamically adjusts two learning factors in the velocity update equation based on the effect of wind on self-cognition and social cognition of a particle. In...
This paper presents a novel Q-learning based auction (QL-BA) algorithm for dynamic spectrum access in a one primary user multiple secondary users (OPMS) scenario. In the auction market, the secondary user provides a bidding price dynamically and intelligently using a Q-learning based bidding strategy to compete for current access opportunity; meanwhile primary user decides to whom to release the unused...
An adaptive resource allocation scheme for QoS oriented OFDMA system, which schedules two different utility functions for the Real-time/Non Real-time traffic simultaneously, is proposed in this paper. Instead of partial consideration of uniform kinds of QoS, we introduce an updating ratio factor to schedule users of heterogeneous traffic. Due to the complex optimization objective, the general convex...
This paper presents an unknown environment robot path planning algorithm. The robot working environments are expressed by grid model; Using digital potential field generated initial path population, and its optimization find the shortest path, and individual evaluation function were processed fitness function both feasible path and unfeasible path fitness function, and then by increasing the deleted...
An evolutionary mechanism of local-competing and global-cooperating is presented for cooperative parallel mechanism based multi-particle-swarm optimizer (CP-MPSO), the competitive relationship between the particles of the traditional serial particle swarm optimizer is analyzed. A weighted-best-information based the PSO with cooperation-characteristic is proposed. Finally, the implementation of CP-MPSO...
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