The Experts below are selected from a list of 23286 Experts worldwide ranked by ideXlab platform
Qifang Luo - One of the best experts on this subject based on the ideXlab platform.
-
Lévy Flight Trajectory-based whale optimization algorithm for engineering optimization
Engineering Computations, 2018Co-Authors: Yongquan Zhou, Ying Ling, Qifang LuoAbstract:This paper aims to represent an improved whale optimization algorithm (WOA) based on a Levy Flight Trajectory and called the LWOA algorithm to solve engineering optimization problems. The LWOA makes the WOA faster, more robust and significantly enhances the WOA. In the LWOA, the Levy Flight Trajectory enhances the capability of jumping out of the local optima and is helpful for smoothly balancing exploration and exploitation of the WOA. It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.,In this paper, an improved WOA based on a Levy Flight Trajectory and called the LWOA algorithm is represented to solve engineering optimization problems.,It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.,An improved WOA based on a Levy Flight Trajectory and called the LWOA algorithm is first proposed.
-
Lévy Flight Trajectory-Based Whale Optimization Algorithm for Global Optimization
IEEE Access, 2017Co-Authors: Ying Ling, Yongquan Zhou, Qifang LuoAbstract:The whale optimization algorithm (WOA) has been shown to be powerful in searching for an optimal solution. This paper proposes an improvement to the whale optimization algorithm that is based on a Levy Flight Trajectory and called the Levy Flight Trajectory-based whale optimization algorithm (LWOA). The LWOA makes the WOA faster and more robust and avoids premature convergence. The Levy Flight Trajectory is helpful for increasing the diversity of the population against premature convergence and enhancing the capability of jumping out of local optimal optima. This method helps obtaining a better tradeoff between the exploration and exploitation of the WOA. The proposed algorithm is characterized by quick convergence and high precision, and it can effectively get rid of a local optimum. The LWOA is further compared with other well-known nature-inspired algorithms on 23 benchmarks and solving infinite impulse response model identification. The statistical results on the benchmark functions show that the LWOA can significantly outperform others on a majority of the benchmark functions, especially in solving an optimization problem that has high dimensionality. Additionally, the superior identification capability of the proposed algorithm is evident from the results obtained through the simulation study compared with other algorithms. All the results prove the superiority of the LWOA.
Ying Ling - One of the best experts on this subject based on the ideXlab platform.
-
Lévy Flight Trajectory-based whale optimization algorithm for engineering optimization
Engineering Computations, 2018Co-Authors: Yongquan Zhou, Ying Ling, Qifang LuoAbstract:This paper aims to represent an improved whale optimization algorithm (WOA) based on a Levy Flight Trajectory and called the LWOA algorithm to solve engineering optimization problems. The LWOA makes the WOA faster, more robust and significantly enhances the WOA. In the LWOA, the Levy Flight Trajectory enhances the capability of jumping out of the local optima and is helpful for smoothly balancing exploration and exploitation of the WOA. It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.,In this paper, an improved WOA based on a Levy Flight Trajectory and called the LWOA algorithm is represented to solve engineering optimization problems.,It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.,An improved WOA based on a Levy Flight Trajectory and called the LWOA algorithm is first proposed.
-
Lévy Flight Trajectory-Based Whale Optimization Algorithm for Global Optimization
IEEE Access, 2017Co-Authors: Ying Ling, Yongquan Zhou, Qifang LuoAbstract:The whale optimization algorithm (WOA) has been shown to be powerful in searching for an optimal solution. This paper proposes an improvement to the whale optimization algorithm that is based on a Levy Flight Trajectory and called the Levy Flight Trajectory-based whale optimization algorithm (LWOA). The LWOA makes the WOA faster and more robust and avoids premature convergence. The Levy Flight Trajectory is helpful for increasing the diversity of the population against premature convergence and enhancing the capability of jumping out of local optimal optima. This method helps obtaining a better tradeoff between the exploration and exploitation of the WOA. The proposed algorithm is characterized by quick convergence and high precision, and it can effectively get rid of a local optimum. The LWOA is further compared with other well-known nature-inspired algorithms on 23 benchmarks and solving infinite impulse response model identification. The statistical results on the benchmark functions show that the LWOA can significantly outperform others on a majority of the benchmark functions, especially in solving an optimization problem that has high dimensionality. Additionally, the superior identification capability of the proposed algorithm is evident from the results obtained through the simulation study compared with other algorithms. All the results prove the superiority of the LWOA.
Yongquan Zhou - One of the best experts on this subject based on the ideXlab platform.
-
Lévy Flight Trajectory-based whale optimization algorithm for engineering optimization
Engineering Computations, 2018Co-Authors: Yongquan Zhou, Ying Ling, Qifang LuoAbstract:This paper aims to represent an improved whale optimization algorithm (WOA) based on a Levy Flight Trajectory and called the LWOA algorithm to solve engineering optimization problems. The LWOA makes the WOA faster, more robust and significantly enhances the WOA. In the LWOA, the Levy Flight Trajectory enhances the capability of jumping out of the local optima and is helpful for smoothly balancing exploration and exploitation of the WOA. It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.,In this paper, an improved WOA based on a Levy Flight Trajectory and called the LWOA algorithm is represented to solve engineering optimization problems.,It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.,An improved WOA based on a Levy Flight Trajectory and called the LWOA algorithm is first proposed.
-
Lévy Flight Trajectory-Based Whale Optimization Algorithm for Global Optimization
IEEE Access, 2017Co-Authors: Ying Ling, Yongquan Zhou, Qifang LuoAbstract:The whale optimization algorithm (WOA) has been shown to be powerful in searching for an optimal solution. This paper proposes an improvement to the whale optimization algorithm that is based on a Levy Flight Trajectory and called the Levy Flight Trajectory-based whale optimization algorithm (LWOA). The LWOA makes the WOA faster and more robust and avoids premature convergence. The Levy Flight Trajectory is helpful for increasing the diversity of the population against premature convergence and enhancing the capability of jumping out of local optimal optima. This method helps obtaining a better tradeoff between the exploration and exploitation of the WOA. The proposed algorithm is characterized by quick convergence and high precision, and it can effectively get rid of a local optimum. The LWOA is further compared with other well-known nature-inspired algorithms on 23 benchmarks and solving infinite impulse response model identification. The statistical results on the benchmark functions show that the LWOA can significantly outperform others on a majority of the benchmark functions, especially in solving an optimization problem that has high dimensionality. Additionally, the superior identification capability of the proposed algorithm is evident from the results obtained through the simulation study compared with other algorithms. All the results prove the superiority of the LWOA.
W. W. Melvin - One of the best experts on this subject based on the ideXlab platform.
-
Wind identification along a Flight Trajectory, part 3: 2D-dynamic approach
Journal of Optimization Theory and Applications, 1993Co-Authors: Angelo Miele, T. Wang, C. Y. Tzeng, W. W. MelvinAbstract:This paper deals with the identification of the wind profile along a Flight Trajectory by means of a two-dimensional dynamic approach. In this approach, the wind velocity components are computed as the difference between the inertial velocity components and the airspeed components. The airspeed profile as well as the nominal thrust, drag, and lift profiles are obtained from the available DFDR measurements. The actual values of the thrust, drag, and lift are assumed to be proportional to the respective nominal values via multiplicative parameters, called the thrust, drag, and lift factors. The thrust, drag, and lift factors plus the inertial velocity components at impact are determined by matching the Flight Trajectory computed from DFDR data with the Flight Trajectory available from ATCR data. This leads to a least-square problem which is solved analytically under the additional requirement of closeness of the multiplicative factors to unity. Application of the 2D-dynamic approach to the case of Flight Delta 191 shows that, with reference to the last 180 sec before impact, the values of the multiplicative factors were 1.09, 0.84, and 0.89; this implies that the actual values of the thrust, drag, and lift were 9% above, 16% below, and 11% below their respective nominal values. For the last 60 sec before impact, the aircraft was subject to severe windshear, characterized by a horizontal wind velocity difference of 123 fps and a vertical wind velocity difference of 80 fps. The 2D-dynamic approach is applicable to the analysis of windshear accidents in take-off or landing, especially for the case of older-generation, shorter-range aircraft which do not carry the extensive instrumentation of newer-generation, longer-range aircraft. The same methodology can be extended to the investigation of aircraft accidents originating from causes other than windshear (e.g., icing, incorrect flap position, engine malfunction), above all if its precision is further increased by combining the 2D-dynamic approach and the 2D-kinematic approach.
-
Wind identification along a Flight Trajectory, part 2: 2D-kinematic approach
Journal of Optimization Theory and Applications, 1993Co-Authors: Angelo Miele, T. Wang, W. W. MelvinAbstract:This paper deals with the identification of the wind profile along a Flight Trajectory by means of a two-dimensional kinematic approach. In this approach, the wind velocity components are computed as the difference between the inertial velocity components and the airspeed components. The airspeed profile is obtained from Flight measurements. The inertial velocity profile is obtained by integration of the measured inertial acceleration. The accelerometer biases and the impact values of the inertial velocity components are determined by matching the computed Flight Trajectory with the measured Flight Trajectory, available from the digital Flight data recorder and air traffic control radar. This leads to a least-square problem, which is solved analytically for both the continuous formulation and the discrete formulation. Key to the precision of the identification process is the proper selection of the integration time. Because the measured data are noise-corrupted, unstable identification occurs if the integration time is too short. On the other hand, if the integration time is too long, the hypothesis of two-dimensional motion (Flight Trajectory nearly contained in a vertical plane) breaks down. Application of the 2D-kinematic approach to the case of Flight Delta 191 shows that stable identification takes place for integration times in the range τ = 120 to 180 sec before impact. The results of the 2D-kinematic approach are close to those of the 3D-kinematic approach (Ref. 1), particularly in terms of the inertial velocity components at impact (within 1 fps) and the maximum wind velocity differences (within 2 fps). The 2D-kinematic approach is applicable to the analysis of wind-shear accidents in take-off or landing, especially for the case of older-generation, shorter-range aircraft which do not carry the extensive instrumentation of newer-generation, longer-range aircraft.
-
Wind identification along a Flight Trajectory, part 1: 3D-kinematic approach
Journal of Optimization Theory and Applications, 1992Co-Authors: Angelo Miele, T. Wang, W. W. MelvinAbstract:This paper deals with the identification of the wind profile along a Flight Trajectory by means of a three-dimensional kinematic approach. The approach is then applied to a recent aircraft accident, that of Flight Delta 191, which took place at Dallas-Fort Worth International Airport on August 2, 1985. In the 3D-kinematic approach, the wind velocity components are computed as the difference between the inertial velocity components and the airspeed components. The airspeed profile is obtained from Flight measurements. The inertial velocity profile is obtained by integration of the measured inertial acceleration. The accelerometer biases and the impact values of the inertial velocity components are determined by matching the computed Flight Trajectory with the measured Flight Trajectory, available from the digital Flight data recorder (DFDR) and air traffic control radar (ATCR). This leads to a least-square problem, which is solved analytically. Key to the precision of the identified wind profile is the correct identification of the accelerometer biases and the impact velocity components. In turn, this depends on the proper selection of the integration time. Because the measured data are noise-corrupted, unstable identification occurs if the integration time is too short. On the other hand, stable identification takes place if the integration time is properly chosen. Application of the method developed to the case of Flight Delta 191 shows that the identification problem has a stable solution if the integration time is larger than 180 sec. Numerical computation shows that, for Flight Delta 191, the maximum wind velocity difference determined with the 3D-kinematic approach was Δ W _ x =124 fps in the longitudinal direction, Δ W _ y =66 fps in the lateral direction, and Δ W _ h =71 fps in the vertical direction.
-
Wind identification along a Flight Trajectory, part 1: 3D-kinematic approach
Journal of Optimization Theory and Applications, 1992Co-Authors: Angelo Miele, T. Wang, W. W. MelvinAbstract:This paper deals with the identification of the wind profile along a Flight Trajectory by means of a two-dimensional dynamic approach. In this approach, the wind velocity components are computed as the difference between the inertial velocity components and the airspeed components. The airspeed profile as well as the nominal thrust, drag, and lift profiles are obtained from the available DFDR measurements. The actual values of the thrust, drag, and lift are assumed to be proportional to the respective nominal values via multiplicative parameters, called the thrust, drag, and lift factors. The thrust, drag, and lift factors plus the inertial velocity components at impact are determined by matching the Flight Trajectory computed from DFDR data with the Flight Trajectory available from ATCR data. This leads to a least-square problem which is solved analytically under the additional requirement of closeness of the multiplicative factors to unity.
Shinji Suzuki - One of the best experts on this subject based on the ideXlab platform.
-
Real-Time Flight Trajectory Generation Applicable to Emergency Landing Approach
TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, 2009Co-Authors: Masahiro Miwa, Takeshi Tsuchiya, Satoshi Yonezawa, Nobuhiro Yokoyama, Shinji SuzukiAbstract:Flight management systems have greatly reduced cockpit workloads, but are not capable of calculating new Flight plans in real time when Flight characteristics vary or when Flight trajectories become nonstationary. This paper presents a real-time Flight Trajectory generator (R-FTG) applicable to emergency landing approaches. First, the R-FTG calculates a preliminary Flight path, which consists of an initial turn, a straight-line Flight, and a terminal turn. The R-FTG then optimizes the preliminary Flight path by using a direct collocation method. In order to give the direct collocation method real-time performance, an idea called stage division is incorporated. Combining the direct collocation and stage division enables real-time generation of near optimal Flight trajectories. Additionally, wind effects are considered in the generating process. The R-FTG is evaluated by numerical simulations; calculation results of the R-FTG are compared with those of an offline optimization method, and the calculation results under different bank angle constraints are examined. The calculations for the wind effects are also studied. These results show the effectiveness of the proposed real-time Flight Trajectory generator.
-
Real-Time Flight Trajectory Optimization and its Verification in Flight
Journal of Aircraft, 2009Co-Authors: Takeshi Tsuchiya, Shinji Suzuki, Kazuya Masui, Masahiro Miwa, Hiroshi TomitaAbstract:T HIS Note presents a real-time Flight Trajectory optimization method. The Flight Trajectory that minimizes the fuel consumption or Flight time of an aircraft can be solved with optimization. Because the optimization is time-consuming, the optimal Flight Trajectory needs to be obtained before Flight. This, however, cannot cope with unexpected situations in Flight. Thus, the real-time optimization, which optimizes the Flight Trajectory with the transition of the Flight state, is important. The final goal of our study is to establish the real-time Trajectory generation applicable to emergency landing approaches. Though the present Flight management system provides the optimal Flight path for a Flight plan in normal operations, it cannot operate in emergency situations. This Note presents a fundamental real-time Trajectory optimization algorithm and its Flight validation. Many studies about real-time Flight-path generation have produced a Flight path by connecting the trim conditions in prestored databases [1,2]. In these studies, computer-assisted simulations were performed, but there were few actual Flight experiments. Additionally, it is difficult to generate nonstational trajectories and the wind effects were not considered. In Japan, the Society of Japanese Aerospace Companies has promoted research on the development of a fault-tolerant Flight control system. In a proceeding study, Suzuki et al. proposed a Flight Trajectory search method composed of a realtime A* algorithm and a random tabu search method [3]. They also conducted Flight experiments. This random-based method, however, lacks convergent stability, so it often does not produce the appropriate Trajectory. We have taken over this study, and in this Note we apply a direct collocation method including some schemes to solve the preceding problems. Actual Flight experiments are also conducted to prove the effectiveness of the method. The experimental aircraft is MuPAL, the Multi-Purpose Aviation Laboratory, developed by JAXA (Japan Aerospace Exploration Agency) [4]. It has a high-precision Global Positioning System/inertial navigation system and a three-axis airspeed sensor. The system allows the estimation of the wind velocity and direction during Flight. MuPALalso has a tunnel-in-the-sky display, which was developed by JAXA [5]. The experiments were conducted under manual tracking control using the display. In the future, the Trajectory generated by the real-time optimization method will be tracked by an automaticFlight control systembeing developed in the research on the fault-tolerant Flight control system.
-
A Study on Online Flight Trajectory Search and its Flight Simulator Testing
AIAA Infotech@Aerospace 2007 Conference and Exhibit, 2007Co-Authors: Satoshi Yonezawa, Shinji Suzuki, Takeshi Tsuchiya, Masahiro Miwa, Nobuhiro YokoyamaAbstract:[Abstract] Real -time Flight Trajectory optimization algorithms are developed and evaluated through numerical simulation and Flight simulator testing. The purpose of this study is to guide and control an aircraft in emergency landing. Though our final goal is to develop an automatic control system for tracking Flight trajectories generated with the online optimization, this study verifies the validity of the generated optimal trajectories with manual Flight control. This paper considers the real-time direct Trajectory optimization method that can deal with constraints more strictly.
-
Online Four-Dimensional Flight Trajectory Search and its Flight Testing
AIAA Guidance Navigation and Control Conference and Exhibit, 2005Co-Authors: Shinji Suzuki, Yutaka Komatsu, Satoshi Yonezawa, Kazuya Masui, Hiroshi TomitaAbstract:Online Flight Trajectory optimization algorithms are developed in order to guide and control aircraft for emergency landing. Further, the applicability of generated Flight trajectories to real Flights is evaluated using a Flight simulator and an experimental aircraft. By combining the real-time A* path search algorithm with the R-TABU optimization method and an inverse dynamic method, a near-optimal four-dimensional Flight Trajectory is computed in real time. The proposed method is applied to design a Flight Trajectory for emergency landing. The generated Flight Trajectory is shown to pilots as a tunnel-in-the-sky image in order to track the Trajectory by manual operation. Both the simulation and Flight experiments refine the algorithms and demonstrate the applicability of the proposed system.
-
simultaneous optimization of sailplane design and its Flight Trajectory
Journal of Aircraft, 1996Co-Authors: Shinji Suzuki, Norihisa KawamuraAbstract:An aircraft design and its Flight Trajectory problem should be formulated simultaneously when an exact Flight mission is determined or an extremely high-performance level is required. This article presents a block diagonal sequential quadratic programming approach by introducing interface variables between the two problems to efficiently solve simultaneous optimization problems. As numerical examples, the design of a sailplane for a Flight distance competition is studied. The need of simultaneous optimization will be demonstrated by comparing a conventional design process; i.e., a lift-drag ratio maximization approach.