By utilising Takagi–Sugeno (T–S) fuzzy set approach, this paper addresses the robust H∞ dynamic output feedback control for the non-linear longitudinal model of flexible air-breathing hypersonic vehicles (FAHVs). The flight control of FAHVs is highly challenging due to the unique dynamic characteristics, and the intricate couplings between the engine and fight dynamics and external disturbance. Because of the dynamics’ enormous complexity, currently, only the longitudinal dynamics models of FAHVs have been used for controller design. In this work, T–S fuzzy modelling technique is utilised to approach the non-linear dynamics of FAHVs, then a fuzzy model is developed for the output tracking problem of FAHVs. The fuzzy model contains parameter uncertainties and disturbance, which can approach the non-linear dynamics of FAHVs more exactly. The flexible models of FAHVs are difficult to measure because of the complex dynamics and the strong couplings, thus a full-order dynamic output feedback controller is designed for the fuzzy model. A robust H∞ controller is designed for the obtained closed-loop system. By utilising the Lyapunov functional approach, sufficient solvability conditions for such controllers are established in terms of linear matrix inequalities. Finally, the effectiveness of the proposed T–S fuzzy dynamic output feedback control method is demonstrated by numerical simulations. 相似文献
In this paper, we use support vector machine to classify the defects in steel strip surface images. After image binarization, three types of image features, including geometric feature, grayscale feature and shape feature, are extracted by combining the defect target image and its corresponding binary image. For the classification model based on support vector machine, we utilize Gauss radial basis as the kernel function, determine model parameters by cross-validation and employ one-versus-one method for multiclass classifier. Experiment results show that support vector machine model outperforms the traditional classification model based on back-propagation neural network in average classification accuracy. 相似文献
An ILRIS-36D 3-D laser image scanning system was used to monitor the Anjialing strip mine slope on Pingshuo in Shanxi province.The basic working principles,performance indexes,features and data collection and processing methods are illustrated.The point cloud results are analyzed in detail.The rescale range analysis method was used to analyze the deformation characteristics of the slope.The results show that the trend of slope displacement is stable and that the degree of landslide danger is low.This work indicates that 3-D laser image scanning can supply multi-parameter,high precision real time data over long distances.These data can be used to study the distortion of the slope quickly and accurately. 相似文献
An integrated co-evolution model with the consideration of land use and traffic network design is proposed in this paper. In the suggested model, two kinds of economic agents are considered. On the one hand, the government makes the investment decision for the traffic network improvement based on the current traffic condition under the limited budget. On the other hand, households and companies will choose their locations according to the attraction of each traffic zone related to the road network accessibility and the housing price. Therefore, the land use is indicated by the population and employment distributions through the evolution process. Besides, the improvement of road capacity is modeled by a general bi-level programming of traffic network design. Simulation experiments show that the city will be more efficient and will have higher average accessibility for employment and population in the evolution process. 相似文献
This paper presents a new delay system approach to network-based control. This approach is based on a new time-delay model proposed recently, which contains multiple successive delay components in the state. Firstly, new results on stability and H∞ performance are proposed for systems with two successive delay components, by exploiting a new Lyapunov-Krasovskii functional and by making use of novel techniques for time-delay systems. An illustrative example is provided to show the advantage of these results. The second part of this paper utilizes the new model to investigate the problem of network-based control, which has emerged as a topic of significant interest in the control community. A sampled-data networked control system with simultaneous consideration of network induced delays, data packet dropouts and measurement quantization is modeled as a nonlinear time-delay system with two successive delay components in the state and, the problem of network-based H∞ control is solved accordingly. Illustrative examples are provided to show the advantage and applicability of the developed results for network-based controller design. 相似文献
Course scheduling is a combinatorial optimization problem with multiple constraints. To achieve the reasonable allocation of teaching resources, all courses should be arranged under a number of specified constraints. With the increased number of courses, the solution space increases exponentially. However, the traditional methods cannot quickly find the optimal solution. In order to overcome the disadvantages of low efficiency and the possibility of high conflict in traditional course scheduling, this research study proposes a course scheduling, method based on an improved binary cuckoo search algorithm (IBCS). First of all, a multi-objective and multi-constraint mathematical model of course scheduling is established. Course scheduling involves issues, such as allocating teachers, courses, classes, classrooms and time under specific constraints. The class element is defined to represent the class and the course that the teachers will teach. Therefore, the problem of course scheduling is transformed into the process of mapping from the class element to the classroom-time pair. Six hard constraints and three soft constraints are also defined accordingly. Then, the BCS algorithm is used to search the best course scheduling scheme in the binary-encoded solution space. In order to control the convergence rate effectively and avoid falling into the local optimum, a dynamically adjustable, equilibrium coefficient is introduced. Therefore, the algorithm retains the diversity of the solutions while converging. Finally, this research study constructs the data set and carries out the simulation experiment. It also compares the IBCS algorithm in this paper with the genetic algorithm and the standard binary cuckoo search algorithm (BCS). Experimental results show that the IBCS algorithm can converge in effective time. Meanwhile, it can achieve an improved global scheduling scheme with higher stability.