Orthogonal learning particle swarm optimization

Particle swarm optimization (PSO) relies on its learning strategy to guide its search direction. Traditionally, each particle utilizes its historical best experience and its neighborhood’s best experience through linear summation. Such a learning strategy is easy to use, but is inefficient when searching in complex problem spaces. Hence, designing learning strategies that can utilize previous search information (experience) more efficiently has become one of the most salient and active PSO research topics. In this paper, we proposes an orthogonal learning (OL) strategy for PSO to discover more useful information that lies in the above two experiences via orthogonal experimental design. We name this PSO as orthogonal learning particle swarm optimization (OLPSO). The OL strategy can guide particles to fly in better directions by constructing a much promising and efficient exemplar. The OL strategy can be applied to PSO with any topological structure. In this paper, it is applied to both global and local versions of PSO, yielding the OLPSO-G and OLPSOL algorithms, respectively. This new learning strategy and the new algorithms are tested on a set of 16 benchmark functions, and are compared with other PSO algorithms and some state of the art evolutionary algorithms. The experimental results illustrate the effectiveness and efficiency of the proposed learning strategy and algorithms. The comparisons show that OLPSO significantly improves the performance of PSO, offering faster global convergence, higher solution quality, and stronger robustness

Effects of several physiochemical factors on cell growth and gallic acid accumulation of Acer ginnala Maxim cell suspension culture

The production of gallic acid in cell suspension culture of Acer ginnala Maxim was studied. Some physiochemical factors and chemical substances effect on the cell growth and the production of gallic acid were investigated. Cells harvested from plant tissue culture were extracted and applied to high performance liquid chromatography to measure gallic acid content. 0.008 mg.L-1 TDZ and 0.1 mg.L-1 BA was optimal for the cell growth. 0.004 mg.L-1 TDZ and 0.1 mg.L-1 BA was best for the production of gallic acid. Maintaining the initial pH value at 5.8 was most suitable for gallic acid accumulation in A. ginnala Maxim cell suspension cultures. To satisfy the condition of mass-producing gallic acid in the suspension culture, the adapted inoculum quantity was 30 g.L-1. The results also provided evidence that the optional culture period was 7 days with light.Key words: Acer ginnala Maxim, gallic acid, cell growth, suspension culture, physiochemical factor

Rotor field orientation speed and torque control of BDFM with adaptive second order sliding mode

This paper presents two cascaded second order sliding mode controllers (SOSMCs) for brushless doubly fed motor (BDFM) adjustable speed system, which regulate the speed and torque. And an adaptive super twisting algorithm is incorporated into the SOSMCs to adaptively regulate the law of SOSMC. The proposed controllers for BDFM eliminate the average chattering encountered by most sliding mode control (SMC) schemes, and also possess the robustness and excellent static and dynamic performances of SMC. Simulation results show that the proposed control strategy is feasible, proper and effective. © 2013 IEEE

Control of redundancy PEM fuel cells in UPS applications with improved performance and durability

© 2013 IEEE. To guarantee the reliable operation of 24 hours, improve the performance and durability of a proton exchange membrane fuel cell (PEMFC) stack, and prevent it from sudden failure in an uninterruptible power system (UPS) with hybrid backup redundancy PEMFCs, battery and supercapacitor (SC) power sources, this paper conducts research in smart power management and control strategy of two PEMFCs and UPS. Firstly, based on the analysis of the major degradation mechanisms of different components of PEMFC against the operation conditions, two PEMFCs are proposed and applied to the UPS system. The experimental results show that the proposed intelligent energy management and control strategy can effectively guarantee the power sources supplied to UPS, and automatically switch the power supply between two PEMFCs

Control of proton exchange membrane fuel cell based on fuzzy logic

This paper presents a control strategy suitable for hydrogen/air proton-exchange membrane fuel cells (PEMFCs), based on the process modeling using fuzzy logic. The control approach is tested using a PEMFC stack consisting of 32 cells with parallel channels. An optimal fuzzy-PI controller is designed to mainly control the hydrogen and air/oxygen mass flows, and auxiliary variables such as the temperature, pressure, humidity of the membrane, and proportion of stoichiometry. The fuzzy logic controller possesses many advantages over the PID controllers, such as a higher performance/cost ratio. It is shown experimentally that the optimal fuzzy-PI controller can improve the voltage and current performance of the system when the load changes

Development of a single-phase high frequency UPS with backup PEM fuel cell and battery

This paper presents a 300 W single-phase high frequency uninterrupted power supply (UPS) with backup proton exchange membrane fuel cell (PEMFC) and battery, DC/AC inverter, DC/DC converter, AC/DC rectifier, and AC/DC recharger. The principle and structure of the PEMFC/battery hybrid UPS system are introduced and discussed. Key practical techniques of the design are presented, including the design of the PEMFC generating system, the control technique of the AC/DC rectifier, AC/DC recharger, DC/AC inverter and DC/DC converter based on a microcomputer MC68HC11K4 and other integrated circuit chips. Experimental results show that during the switching process from battery to PEMFC, and vice versa, the UPS can provide an uninterrupted alternate voltage for the load, with low cost, low weight, small volume and size, great reliability and maintainability

Comprehensive control of proton exchange membrane fuel cell as backup power supply for UPS

To improve the performance of a proton exchange membrane fuel cell (PEMFC) stack, it is important to avoid the hydrogen and oxygen/air starvation of electrochemical reaction, prevent the dehydration and drying of the membrane, and track the output power. This paper conducts research in a comprehensive control strategy of the operation parameters of an uninterruptible power system (UPS) with backup PEMFC and battery power sources, such as the thermal management and control of operating temperature, pressures and mass flows of hydrogen and air for the PEMFC stack, switch of the power supply between PEMFC and battery for UPS, and the output power tracking of PEMFC. Based on the dynamic model of the anode and cathode flow system, the models of manifold and the performance curve, a detail model analysis is presented. A comprehensive control method is proposed and applied to the PEMFC system employed for the power source of UPS. The experimental results show that the comprehensive control method can effectively keep constant pressures of the inlet hydrogen and air, automatically switch the power supply between PEMFC and battery, reasonably improve the performance of the PEMFC through thermal management and control of operating temperature, and track the real-time changes of the output power and the distribution of the mass flows of hydrogen and oxygen/air

Grey Fuzzy Sliding Mode Control with Grey Estimator for Brushless Doubly Fed Motor

In this paper, a grey fuzzy sliding mode controller (GFSMC) for brushless doubly fed motor (BDFM) adjustable speed system is presented. A grey model estimator and adaptive fuzzy control technology are incorporated into the sliding mode control (SMC) to adaptively regulate the adaptive law of SMC. The proposed adaptive fuzzy equivalent controller, adaptive fuzzy switching controller, and grey model compensation controller for BDFM can eliminate the average chattering encountered by most SMC schemes, improve the robustness, and obtain excellent static and dynamic performances of SMC. Simulation results show that the proposed control strategy is feasible, correct and effective

An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficienc