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Khodabakhshian, Amin; Daryabeigi, Ehsan; Moazzami, Majid
doi: 10.1177/0037549713495741pmid: N/A
This paper presents a new optimization method for designing the parameters of a power system stabilizer (PSS) using a smart bacteria foraging algorithm (SBFA). The proposed technique, which is a modification of the bacteria foraging method (BFA), can direct bacteria by performing a tumble with a smart unit of length, decreasing the cost function better than the conventional BFA method. This algorithm not only considers social intelligence, but also emphasizes the individual intelligence of bacteria for finding a better nutritional path. A new cost function in the proposed SBFA has been used for specifying the direction of movement after a tumble. This approach led to a higher convergence speed and also better performance than the BFA. The effectiveness of the proposed method has been tested on a multi-machine power system while considering a frequency error-based objective function to enhance damping of the electromechanical oscillation modes. Simulation results for the proposed method are compared with conventional PSS, BFA- and fuzzy-based PSS methods. The results show the superior performance of the proposed SBFA-based PSS in comparison with other techniques for damping power system oscillations.
Eguia, Ignacio; Racero, Jesus; Guerrero, Fernando; Lozano, Sebastian
doi: 10.1177/0037549713491590pmid: N/A
A reconfigurable cellular manufacturing system (RCMS) consists of multiple reconfigurable machining cells, each of which has one or more reconfigurable machine tools (RMTs), a setup station, and an automatic material handling and storage system. As part of the RCMS design process, similar parts must be grouped into part families and the RMTs must be arranged to form parallel cell configurations. A RCMS is designed at the outset for rapid changes in its components, allowing the production of multiple part families in each parallel cell. This paper proposes a new approach to simultaneously solve the cell formation and the scheduling of part families for an effective working of a RCMS. A new mixed integer linear programming model is used to represent both problems at the same time with the objective of minimizing production costs. Two types of production costs are considered: reconfiguration (i.e. setup) costs for changing from one family to the next one, and under-utilization costs for not using the RMT resources. A small size example is used to illustrate this integrated methodology. Computational experiments have been carried out adapting some larger instances from the literature on cellular manufacturing systems. Solving large instances optimally becomes prohibitive in terms of computational effort. That is why an approximate method, based on a Tabu search (TS) algorithm, has also been developed. Results show the ability of this algorithm to find good-quality production schedules of part families in a RCMS without requiring long computing times. It can be concluded that a RCMS can attain manufacturing flexibility without losing cost-effectiveness and that the approach proposed in this paper can efficiently solve real-world problems.
Czop, Piotr; Sławik, Damian; Wszołek, Grzegorz
doi: 10.1177/0037549713486012pmid: N/A
The aim of this paper is to provide a mathematical method for minimizing the vibrations produced by hydraulic dampers, while maintaining the same damping force characteristics. The vibration level depends on the force–pressure characteristics of valve systems, which determine the damping force and high-frequency acceleration characteristic of a damper, and which need to be optimally tuned to lower the noise level. The paper considers a model-based approach to obtain the optimal pressure–flow characteristic via simulations conducted with the use of coupled models, including the damper and the servo-hydraulic tester model. The objectives of this work were as follows: (i) develop or adapt a double-tube damper model including pressure–flow valve characteristics; (ii) define key parameters of the valve characteristics influencing the high-frequency piston-rod acceleration, which is considered as a measure of vibration level; (iii) identify the parameter values (trends) minimizing the piston-rod acceleration using two alternative methods, namely a quick-and-dirty method based on a design of experiment (DOE) plan and a nonlinear programming method; (iv) obtain the optimal pressure–flow characteristic minimizing the vibration level by means of simulation; and (v) perform an experimental study comparing the high-frequency content of acceleration produced by the damper assembled with the original and optimized valve system using a laboratory setup.
doi: 10.1177/0037549713485899pmid: N/A
Work related to the tuning of the first-principle model of a feedwater heater operating in a coal-fired power unit is presented, along with discussion concerning the most efficient and accurate tuning algorithms based on direct-search, first- and second-order optimization techniques. The objective of this work is to find the most efficient and accurate algorithm to tune the model parameters, that is, heat transfer coefficients based on the algorithms’ benchmarking study. The model variables (e.g. variability of the power rate of energy exchange) and estimated parameter values were used to formulate key performance indicators intended for a model-driven diagnostics approach. The computational process was organized in an iterative process of updating model parameters and indicators. The validation was successfully performed using operational data from a 225 MW coal-fired power unit.
Felez, Jesus; Maroto, Joaquin; Cabanellas, Jose M; Mera, Jose M
doi: 10.1177/0037549713483557pmid: N/A
This paper describes a model capable of simulating large-scale traffic in an urban environment. The goal is of this work is the realistic and detailed simulation of the traffic, reproducing the behavior of each vehicle involved in the environment individually. This model has been developed in order to be integrated in an immersive driving simulator, where the driving position is the center of the simulation and the traffic model reproduces what happens around them. The general behavior of the traffic model is based on the following theory. Depending on the size of the urban environment to be simulated, the number of vehicles involved, and the traffic density, the environment can be studied as a whole or segmented in adjacent areas. Each vehicle model has two components. First, the behavior of the vehicle is simulated individually, modeling acceleration and braking, depending on the type and characteristics of each vehicle (mass, power, size, etc.). Second, the behavior of the drivers is also modeled, by type (passive, moderate, aggressive), playing various maneuvers also common in urban traffic circulation, such as lane changes, behavior at crossings and intersections, etc. A traffic light regulation model and the complete signposting of the urban environment are also included. As a result, the developed traffic model is applicable to large-scale traffic simulation integrated in an immersive driving simulator and is very useful when investigating complex behaviors of these environments. The model has been validated comparing it with results obtained from various references and very satisfactory results have been obtained.
Hagendorf, Olaf; Pawletta, Thorsten; Larek, Roland
doi: 10.1177/0037549713500066pmid: N/A
In engineering, a broad range of environments exist for modeling and simulation with integrated parameter optimization. The established techniques only optimize model parameter values, the model structure is considered to be fixed. As system performance is optimized, one may have to redesign the model structure. The redesign is done manually by an analyst. The suboptimal combination of automatic parameter optimization and manual structural changes leads to an optimization task that is prone to error. This paper details an approach that provides optimization through automatic reconfiguration of both the model structure and model parameters. An optimization method that uses an evolutionary algorithm is supported by a model management method. This method is based on the system entity structure/model base framework. The admissible model structures and their associated model parameter sets are specified using the system entity structure ontology. Basic dynamic model components are organized in a model base. In addition to this, new algorithms are introduced. These map knowledge coded in the system entity structure to a set of numerical (structure) parameters, and also perform this mapping in reverse. In this manner a combined structure and parameter optimization problem is derived. Since both methods – evolutionary algorithm and model management – work together concurrently, different system configurations can be evaluated automatically. The objective is to provide an optimal solution; a model optimized for both parameter and structure.
Kuperman, Alon; Zhong, Qing-Chang
doi: 10.1177/0037549712469842pmid: N/A
A nonlinear robust control strategy is proposed in this paper to deal with wing rock motion. The method is based on the disturbance observer enforced contraction theory results. The disturbance observer calculates and robustly cancels system uncertainties and input disturbances. The information regarding the known part of the nonlinear plant dynamics is used by the controller, while the uncertainties and disturbances are treated as an additional input to the system and dealt with by the disturbance observer. The algorithm demonstrates good performance in damping the oscillations while rejecting the disturbances. Simulations are provided to demonstrate the effectiveness of the proposed method via an application to an experimentally derived delta wing rock model operating in both nominal and uncertain environments.
Lian, Jing; Han, Hu; Li, Linhui; Zhou, Yafu; Feng, Jian
doi: 10.1177/0037549713489725pmid: N/A
Energy saving and environmental protection are the two main themes of today’s auto industry development. The hybrid electric vehicle (HEV) has become one of the most practical significant ways to solve energy and emission problems with good fuel economy and lower emissions. Aimed at the present HEV control methods, which have problems such as power loss, low efficiency of the system, the deterioration of the lubrication conditions, and so on, from the points of view of the overall efficiency of drive system, an optimal control method for a HEV is proposed to solve these problems. Firstly, all the possible operating modes are formulated. Then the efficiency evaluation equations of different modes are constructed. Next, according to the battery state of charge, this method determines the possible operating modes, and then the efficiency of different modes is calculated by means of the demand torque. Comparing the efficiency of different modes, the mode with the highest efficiency is obtained so that the engine torque and motor torque are distributed to enable the engine and motor output to correspond with this torque. Finally, the proposed method is simulated; the results show that it reduces system power loss and vehicle fuel consumption and emissions, and that it also protects the life of the transmission parts and lubrication conditions to some extent, achieving significant improvements.
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