An optimal guidance algorithm for air-breathing launch vehicle is proposed based on optimal trajectory correction. The optimal trajectory correction problem is a nonlinear optimal feedback control problem with state i...
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An optimal guidance algorithm for air-breathing launch vehicle is proposed based on optimal trajectory correction. The optimal trajectory correction problem is a nonlinear optimal feedback control problem with state inequality constraints which results in a nonlinear and nondifferentiable two-point boundary value problem (TPBVP). It is difficult to solve TPBVP on-board. To reduce the on-board calculation cost, the proposed guidance algorithm corrects the reference trajectory in every guidance cycle to satisfy the optimality condition of the optimal feedback control problem. By linearizing the optimality condition, the linear TPBVP is obtained for the optimal trajectory correction. The solution of the linear TPBVP is obtained by solving linear equations through the Simpson rule. Considering the solution of the linear TPBVP as the searching direction for the correction values, the updating step size is generated by linear search. Smooth approximation is applied to the inequality constraints for the nondifferentiable Hamiltonian. The sufficient condition for the global convergence of the algorithm is given in this paper. Finally, simulation results show the effectiveness of the proposed algorithm.
Recommender systems are used to make recommendations about products, information, or services for users. Most existing recommender systems implicitly assume one particular type of user behavior. However, they seldom c...
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Recommender systems are used to make recommendations about products, information, or services for users. Most existing recommender systems implicitly assume one particular type of user behavior. However, they seldom consider user-recommender interactive scenarios in real-world environments. In this paper, we propose a hybrid recommender system based on user-recommender interaction and evaluate its performance with recall and diversity metrics. First, we define the user-recommender interaction. The recommender system accepts user request, recommends N items to the user, and records user choice. If some of these items favor the user, she will select one to browse and continue to use recommender system, until none of the recommended items favors her. Second, we propose a hybrid recommender system combining random and k-nearest neighbor algorithms. Third, we redefine the recall and diversity metrics based on the new scenario to evaluate the recommender system. Experiments results on the well-known MovieLens dataset show that the hybrid algorithm is more effective than nonhybrid ones.
The Saint-Venant equations of open-channel flow were linearized using the Taylor series and a finite-difference approximation of the original nonlinear, partial differential equations. Using the linear optimal control...
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The Saint-Venant equations of open-channel flow were linearized using the Taylor series and a finite-difference approximation of the original nonlinear, partial differential equations. Using the linear optimal control theory, a proportional-plus-integral (PI) controller was developed for an irrigation canal with five pools. Since the order of the controller gain matrix was large, the Kalman filter was designed to estimate values for the state variables that were not measured. For this problem, there were a total of 45 state and five control variables. With two flow depth measurements per pool, values for the remaining 35 state variables were estimated using the Kalman filter. The simulated canal dynamics with the regional PI controllers along with the local Kalman filter were compared with the performance of the global control algorithms for achieving a constant-volume control and a constant-level control of an example irrigation canal. The performance of the regional constant-volume control algorithms was found to be as good as the performance of the global control algorithm, whereas the performance of the regional constant-level control algorithm was marginally acceptable.
The success to design a hybrid optimization algorithm depends on how to make full use of the effect of exploration and exploitation carried by agents. To improve the exploration and exploitation property of the agents...
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The success to design a hybrid optimization algorithm depends on how to make full use of the effect of exploration and exploitation carried by agents. To improve the exploration and exploitation property of the agents, we present a hybrid optimization algorithm with both local and global search capabilities by combining the global search property of rain forest algorithm (RFA) and the rapid convergence of PSO. Originally two kinds of agents, RFAAs and PSOAs, are introduced to carry out exploration and exploitation, respectively. In order to improve population diversification, uniform distribution and adaptive range division are carried out by RFAAs in flexible scale during the iteration. A further improvement has been provided to enhance the convergence rate and processing speed by combining PSO algorithm with potential guides found by both RFAAs and PSOAs. Since several contingent local minima conditions may happen to PSO, special agent transformation is suggested to provide information exchanging and cooperative coevolution between RFAAs and PSOAs. Effectiveness and efficiency of the proposed algorithm are compared with several algorithms in the various benchmark function problems. Finally, engineering design optimization problems taken from the gait control of a snake-like robot are implemented successfully by the proposed RFA-PSO.
The article presents a method for preserving the privacy of individuals while simultaneously making data sets containing their private information available for statistical analysis. The concept of differential privac...
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The article presents a method for preserving the privacy of individuals while simultaneously making data sets containing their private information available for statistical analysis. The concept of differential privacy is said to offer a means of achieving statistical disclosure control, by randomizing responses in a way which preserves the accuracy of the data while dissociating it from the identity of any given individual. The hazards of auxiliary data, which can be used to indirectly ascertain redacted information, are noted, and the usefulness of pan-private algorithms is discussed.
This paper presents the feasibility and effectiveness of magnetorheological (MR) braces in earthquake hazard mitigation. In doing so, a nondimensional variable, beta, which is the ratio of the yield force of the MR da...
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This paper presents the feasibility and effectiveness of magnetorheological (MR) braces in earthquake hazard mitigation. In doing so, a nondimensional variable, beta, which is the ratio of the yield force of the MR damper to forcing input (the product of a characteristic mass of the building and the seismic acceleration) is used to design the MR damper preventing the locked damper motion that may worsen seismic response of the building. Front this theoretical analysis, the activation gap of the damper as an important design parameter to prevent the locked damper motion is chosen. Based on this analysis, the MR damper is fabricated by modifying the commercial MR damper of Lord Corporation, SD-1000-1. Then, a three-story building with MR braces is constructed and its dynamic equation is theoretically derived. In order to investigate semi-active control methods to MR braces, three different control algorithms are formulated and evaluated both numerically and experimentally. The results show that control of the building with semi-actively controlled MR braces is very effective.
Simulated annealing (SA) algorithm is a popular intelligent optimization algorithm which has been successfully applied in many fields. Parameters' setting is a key factor for its performance, but it is also a tedi...
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Simulated annealing (SA) algorithm is a popular intelligent optimization algorithm which has been successfully applied in many fields. Parameters' setting is a key factor for its performance, but it is also a tedious work. To simplify parameters setting, we present a list-based simulated annealing (LBSA) algorithm to solve traveling salesman problem (TSP). LBSA algorithm uses a novel list-based cooling schedule to control the decrease of temperature. Specifically, a list of temperatures is created first, and then the maximum temperature in list is used by Metropolis acceptance criterion to decide whether to accept a candidate solution. The temperature list is adapted iteratively according to the topology of the solution space of the problem. The effectiveness and the parameter sensitivity of the list-based cooling schedule are illustrated through benchmark TSP problems. The LBSA algorithm, whose performance is robust on a wide range of parameter values, shows competitive performance compared with some other state-of-the-art algorithms.
Evaluation of subjective examinations using computerized tools has been a topic of research for more than four decades. Several statistical and mathematical techniques have been proposed by various researchers. In thi...
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Evaluation of subjective examinations using computerized tools has been a topic of research for more than four decades. Several statistical and mathematical techniques have been proposed by various researchers. In this research work, the several methods proposed earlier like Latent Semantic Analysis (LSA), Generalized Latent Semantic Analysis (GLSA), Bilingual Evaluation Understudy (BLEU), and Maximum Entropy (MaxEnt) are compared on common input data. The techniques are implemented using Java programming language, MatLab, and other open source tools. Experiments have been conducted and developed prototypes are tested using a database of 4500 answers with approximately 50 questions of computer science. Comparison of these techniques on a common database is not available in the literature as far as the authors' review is concerned. The database used for testing is collected by conducting tests of students of graduate level in the field of computer science. The pros and cons of each technique on the basis of experiments are discussed in the paper.
A control scheme was developed for the automation of toluene removal in a cyclical bioreactor. Toluene was added to the self-cycling fermenter by diffusion across a silicone membrane. Transient dissolved oxygen, carbo...
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A control scheme was developed for the automation of toluene removal in a cyclical bioreactor. Toluene was added to the self-cycling fermenter by diffusion across a silicone membrane. Transient dissolved oxygen, carbon dioxide evolution, and oxidation-reduction potential (ORP) were screened as potential control variables. Through experimentation, ORP was deemed most effective. Control algorithms based on realtime estimates of the first and second derivatives of the ORP signal were tested. Although both approaches resulted in stable operation of the reactor, average toluene removal efficiencies of 95% were realized when control was based on the second derivative. This was significantly higher than the 77% efficiencies obtained when the control scheme centered on the first derivative of the transient ORP signal. The system developed was self-regulating, ensuring that a high toluene removal rate, on the order of 1.1 g h(-1), was maintained from cycle to cycle.
In this paper, a robust digital image watermarking algorithm is proposed based on fuzzy support vector machine (FSVM) correction. The significant bitplane image is extracted from original host, and undecimated discret...
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In this paper, a robust digital image watermarking algorithm is proposed based on fuzzy support vector machine (FSVM) correction. The significant bitplane image is extracted from original host, and undecimated discrete wavelet transform (UDWT) is performed on the significant bitplane image. The lowpass subband is divided into small blocks, and digital watermark is embedded into original host by adaptively modulating the selected wavelet coefficients in small blocks. In order to resist geometric distortion attacks, FSVM is utilized to learn geometric distortion parameters by using low order Zernike moments. The watermark extraction is carried out after watermarked image has been synchronized without original host. Simulation also shows outstanding robustness of the proposed algorithm against most common image processing operations and geometric distortions. (C) 2012 Elsevier Ltd. All rights reserved.
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