In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple sc...
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作者：
Na LuoFeng QianAutomatic Institute
Key Laboratory of Advanced Control and Optimization of Chemical Processes Ministry of Education State-Key Laboratory of Chemical Engineering East China University of Science and Technology Shanghai China
Estimation of Distribution Algorithm is a new population based evolutionary optimization method and it generates new population from probability distribution model. Like most evolutionary algorithms, it is easy to tra...
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Estimation of Distribution Algorithm is a new population based evolutionary optimization method and it generates new population from probability distribution model. Like most evolutionary algorithms, it is easy to trap into local optimums. In order to avoid this shortcoming, Gaussian and Cauchy probability density function are mixed as probability distribution model. For continuous problems, a new estimation of distribution algorithm sampling under the mixed model is presented. New individuals are generated not only from Gaussian distribution but sometimes from Cauchy distribution in order to keep diversity. The selection strategy of Gaussian and Cauchy distribution are also discussed. The new algorithm is tested on five benchmark functions and results are compared with basic and estimation of distribution algorithm with Cauchy mutation.
We consider the problem of controlling marginally stable linear systems using bounded control inputs for networked control settings in which the communication channel between the remote controller and the system is un...
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ISBN:
(纸本)9781424477456
We consider the problem of controlling marginally stable linear systems using bounded control inputs for networked control settings in which the communication channel between the remote controller and the system is unreliable. We assume that the states are perfectly observed, but the control inputs are transmitted over a noisy communication channel. Under mild hypotheses on the noise introduced by the control communication channel and large enough control authority, we construct a control policy that renders the state of the closed-loop system mean-square bounded.
In this paper, a decentralized control algorithm is proposed for a group of nonholonomic vehicles to form a class of collective circular motion behavior. Without the guidance of a global position reference or a beacon...
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ISBN:
(纸本)9781424477456
In this paper, a decentralized control algorithm is proposed for a group of nonholonomic vehicles to form a class of collective circular motion behavior. Without the guidance of a global position reference or a beacon, the desired collective behavior occurs provided that the multi-agent system is jointly-connected. Moreover, a repulsion mechanism is considered to improve the distribution evenness of the agents' circular motion phases and hence to avoid collision. The effectiveness of the approach is verified through both theoretical analysis and numerical simulation.
A novel individual-based alignmen/repulsion algorithm is proposed in this paper for a flock of multiple agents. With this algorithm, each individual repels its sufficiently close neighbors and aligns to the average ve...
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A novel individual-based alignmen/repulsion algorithm is proposed in this paper for a flock of multiple agents. With this algorithm, each individual repels its sufficiently close neighbors and aligns to the average velocity of its neighbors with moderate distances. In both mathematical analysis and numerical simulation, we prove that the algorithm guarantees an uncrowded flocking behavior with asymptotical velocity synchronization when sufficiently intensive communication exists within the agents. Moreover, we provide the conditions for collision avoidance along the whole transient procedure. The proposed flocking model has its references in natural collective behaviors like escaping panic and traffic jam motions.
Model Predictive Direct Torque control (MPDTC) is a recent computational control methodology that combines the merits of Model Predictive control (MPC) with the ones of Direct Torque control (DTC). Specifically, with ...
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Model Predictive Direct Torque control (MPDTC) is a recent computational control methodology that combines the merits of Model Predictive control (MPC) with the ones of Direct Torque control (DTC). Specifically, with respect to standard DTC, the converter's switching frequency and/or losses are considerably reduced, while at the same time the Total Harmonic Distortion (THD) levels of the phase currents and the torque are improved. Moreover, DTC's favorable dynamic and robustness properties are preserved. This paper presents an MPDTC scheme for a permanent magnet synchronous motor that achieves long prediction horizons in the range of up to 150 time-steps through the use of extrapolation and bounds. A discrete-time internal controller model of the drive system is derived from the physical equations. Simulation results for a three-level voltage source inverter indicate that such an MPDTC scheme, compared to an industry standard controller, is capable of reducing the switching losses and the switching frequency by up to 50%, and the torque THD by 25%, while leaving the current THD unchanged.
Randić et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation and ...
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Randić et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation and prove that the claim is correct, and that it also avoids degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the spectral representation. The method adopts M value to characterize a graphical representation and uses 24-component vector as descriptor. The approach is illustrated on the complete coding sequence of beta-globin genes from 7 different species.
In this paper, sensors, which are directly installed on the surface of the mill, are used to collect mill's signals by wireless. The frame of the system is introduced and the hardware and software is designed in d...
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In this paper, sensors, which are directly installed on the surface of the mill, are used to collect mill's signals by wireless. The frame of the system is introduced and the hardware and software is designed in details in this paper. With the transmission mode of I 2 S and MCU of AT89S2051, the transform from analog signals to digital signals , data's transmission by wireless is achieved by this system. On this basis, the program designed is not only good at collect mill's signals, but also restraining the interference, analyzing spectrum. So the program can effectively achieve the mill state detection.
An algorithm for hybrid optimal control is proposed that varies the discrete state sequence based on gradient information during the search for an optimal trajectory. The algorithm is developed for hybrid systems with...
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ISBN:
(纸本)9781424477456
An algorithm for hybrid optimal control is proposed that varies the discrete state sequence based on gradient information during the search for an optimal trajectory. The algorithm is developed for hybrid systems with partitioned state space. It uses a version of the hybrid minimum principle that allows optimal trajectories to pass through intersections of switching manifolds, which enables the algorithm to vary the sequence. Consequently, the combinatorial complexity of former algorithms can be avoided, since not each possible sequence has to be investigated separately anymore. The convergence of the algorithm is proven and a numerical example demonstrates the efficiency of the algorithm.
The hybrid minimum principle (HMP) gives necessary conditions to be satisfied for optimal solutions of a hybrid dynamical system. In particular, the HMP accounts for autonomous switching between discrete states that o...
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ISBN:
(纸本)9781424477456
The hybrid minimum principle (HMP) gives necessary conditions to be satisfied for optimal solutions of a hybrid dynamical system. In particular, the HMP accounts for autonomous switching between discrete states that occurs whenever the trajectory hits switching manifolds. In this paper, the existing HMP is extended for hybrid systems with partitioned state space to provide necessary conditions for optimal trajectories that pass through an intersection of switching manifolds. This extension is especially useful for the numerical solution of hybrid optimal control problems as it allows for algorithms with significant reduction of computational complexity. Algorithms based on previous versions of the HMP solve separate optimal control problems for each possible sequence of discrete states. The extension enables us to consider the optimal sequence as subject of optimal control that is varied and finally determined during a single optimization run. A first numerical result illustrates the effectiveness of an algorithm based on the extended HMP.
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