Coevolutionary particle swarm optimization(CPSO) algorithm has been investigated and applied in the real world *** tackling the large-scale and complex real time optimization problems,the running time of CPSO algori...
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ISBN:
(纸本)9781538629185
Coevolutionary particle swarm optimization(CPSO) algorithm has been investigated and applied in the real world *** tackling the large-scale and complex real time optimization problems,the running time of CPSO algorithm is a *** this paper,Graphics processing Unit(GPU) is introduced to provide speedup in order to meet the real time *** CPSO algorithm has been implemented on GPU concurrently using the CUDA *** performance and run time of CPU-based and GPU-based CPSO algorithms are compared in *** experiment result shows that the GPU-based parallel computation mode can shorten the run time of CPSO algorithm apparently.
In this paper,the finite-time boundedness(FTB) problem of sliding mode control(SMC) is investigated for a class of switched delay systems subject to uncertain parameter and nonlinear perturbation.A SMC law is cons...
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ISBN:
(纸本)9781538629185
In this paper,the finite-time boundedness(FTB) problem of sliding mode control(SMC) is investigated for a class of switched delay systems subject to uncertain parameter and nonlinear perturbation.A SMC law is constructed to drive the state trajectories onto the integral sliding surface during a finite time *** FTB of the controlled systems on both reaching phase and siding motion phase are analyzed by means of average dwell time ***,a numerical example is given.
This paper proposes a sliding mode estimation-based control to solve the stochastic time delay problem in networked microgrid,because stochastic delay has a great impact on the stability and performance of large power...
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ISBN:
(纸本)9781538629185
This paper proposes a sliding mode estimation-based control to solve the stochastic time delay problem in networked microgrid,because stochastic delay has a great impact on the stability and performance of large power grids(LPG).To analyze the delay effects,the microgrid system model is derived according to the characteristics of the inverter in grid-connected *** on the microgrid system model,the stochastic delay estimation with learning parameter and delayed states are *** control signal designed by sliding mode control(SMC) and the learning parameter of delay estimation are adaptively changed in the sliding mode estimation-based control *** reaching law(ERL) is proposed to solve the chattering issues of *** 3.3 KW microgrid parameters are added into simulation to verify the effectiveness and performance of the proposed control strategy.
Rain Water Algorithm is a new algorithm that inspired by the pattern of physically rain water movements from air to the lowest place on the earth. It is necessary to evaluate the new algorithm with other algorithm uti...
Rain Water Algorithm is a new algorithm that inspired by the pattern of physically rain water movements from air to the lowest place on the earth. It is necessary to evaluate the new algorithm with other algorithm utilizing known mathematical function that available in Comparing Continuous Optimizers (COCO) especially Black Box optimization Benchmarking (BBOB) to analyze the performance of proposed algorithm. optimization results exhibit that the purposed algorithm has surpass performance than others algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA).
Several metal terephthalates were synthesized by hydrothermal solvent method. Firstly, the coordination type of metal ions and carboxylates in terephthalate was studied by FTIR spectroscopy. The results showed that th...
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Several metal terephthalates were synthesized by hydrothermal solvent method. Firstly, the coordination type of metal ions and carboxylates in terephthalate was studied by FTIR spectroscopy. The results showed that the binding type of zinc terephthalate and aluminum terephthalate are mainly bridged coordination, while the chelating coordination mode dominated in the magnesium terephthalate and cerium terephthalate. Secondly, the thermal decomposition mechanism of zinc terephthalate in nitrogen atmosphere was studied by TG and Py-GC/MS techniques. Finally, the activation energy of the thermal decomposition process was obtained by the Friedman method and the Flynn-Wall-Ozawa(FWO) method, and the most probabilistic function was obtained by multiple linear fitting. The results showed that the decomposition process of zinc terephthalate was an one-step reaction and the activation energy was equal to 187.38 kJ/mol.
Considering the imprecise nature of the data in real-world problems, the earliness/tardiness (E/T) fiowshop scheduling problem with uncertain processing time and distinct due windows is concerned in this paper. A fu...
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Considering the imprecise nature of the data in real-world problems, the earliness/tardiness (E/T) fiowshop scheduling problem with uncertain processing time and distinct due windows is concerned in this paper. A fuzzy scheduling model is established and then transformed into a deterministic one by employing the method of maximizing the membership function of middle value. Moreover, an effective scatter search based particle swarm optimization (SSPSO) algorithm is proposed to minimize the sum of total earliness and tardiness penalties. The proposed SSPSO algorithm incorporates the scatter search (SS) algorithm into the frame of particle swarm optimization (PSO) algorithm and gives full play to their characteristics of fast convergence and high diversity. Besides, a differential evolution (DE) scheme is used to generate solutions in the SS. In addition, the dynamic update strategy and critical conditions are adopted to improve the performance of SSPSO. The simulation results indicate the superiority of SSPSO in terms of effectiveness and efficiency.
Hybrid short path evaporation (HSPE) is proposed as an alternative separation process with potentiality for recovery and concentration of thermally unstable molecules such as lactic acid. This work aimed to analyze th...
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In this paper, the tracking performance limitation of networked control systems (NCSs) is studied. The NCSs is considered as continuous-time linear multi-input multi-output (MIMO) systems with random reference noises....
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Economic dispatch is one of the fundamental problems in the power system research. The existing algorithms are either discrete iterative algorithms or continuous-time dynamical algorithms. By virtue of the hybrid tech...
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This paper presents a fuzzy-model-based method for solving the consensus problem of a class of nonlinear multi-agent systems (MASs) with input saturation. Since each agent has nonlinear dynamics, the system is not asy...
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This paper presents a fuzzy-model-based method for solving the consensus problem of a class of nonlinear multi-agent systems (MASs) with input saturation. Since each agent has nonlinear dynamics, the system is not asymptotically null controllable with bounded controls (ANCBC). Therefore, the widely-used low-gain feedback method for designing consensus protocols of MASs with input saturation can no longer work. To this end, the Takagi-Sugeno (T-S) fuzzy model is adopted to formulate the error dynamics of those nonlinear follower agents with input saturation as well as a leader with time-varying states. Accordingly, by using the properties of convex hull, a set of invariance condition in the format of linear matrix inequality (LMI) is designed. Furthermore, by enlarging the shape reference set, the estimation of the attraction domain can be obtained. Simultaneously, by viewing the control gain as an extra free parameter in the LMI optimization procedure, the leader-follower consensus algorithm is proposed, which guarantees that all followers with input saturation can track the leader, and they can asymptotically reach consensus. Finally, numerical experiments validate the effectiveness of the proposed anti-saturation consensus algorithm.
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