— Based on natural ventilation design scheme for an indoor substation, different air distribution schemes were obtained by changing height and size of air inlets and outlets. For indoor substation, three-dimensional simulation of air distribution was conducted by using Computational Fluid Dynamics (CFD) method. Ventilation & cooling effect of different indoor ventilation schemes were simulated with software (Fluent). By analyzing velocity fields and temperature fields, influences of different design parameters on safety and reliability of main transformer room of indoor substation were compared and analyzed in details. Additionally, characteristics and change rules of air distribution with different parameter variations were concluded. Considerations of ventilation organization design for main transformer room of indoor substation and recommendation for better air distribution schemes were provided. The research results also offered some guidance for design and renovation of ventilation & cooling projects of indoor substation.
Based on the working principle of multibeam bathymetric system, this paper establishes a multibeam line design optimization model and coverage width geometric model by establishing a spatial right-angled coordinate system, dichotomy method, moving surface method and other methods. A two-dimensional geometric model of the coverage width and the overlap rate of adjacent strips is established in the two-dimensional plane. Then, based on the geometric model, the relationship equations of seawater depth at the centre of different lines are obtained by triangulation, and then the sine equations of seawater depth at the centre of the line, coverage width and coverage rate are obtained by the sine theorem. Then the equations of the line plane, the multibeam plane and the seabed slope are solved in 3D space, and finally the geometric model of the line perpendicular to the gradient and the optimisation model of the line parallel to the gradient are established respectively. Finally, comparing the total lengths of the lines in the two directions, it is determined that the line direction is east-west, the total number of lines is 34, the total length of the lines is 125936m, and the interval between the lines decreases with the increase of gradient.
A predictive control algorithm is presented in this paper for spacecraft attitude maneuver with nonconvex geometric constraint and bounded inputs.The nonconvex property of the geometric constraint is proved based on the analysis of its Hessian matrix.Then the transformation from nonconvex constraint to convex one is presented by constructing positive definite Hessian matrix.Consequently,a predictive control algorithm for spacecraft attitude maneuver is presented,and it can readily obtain global solution,as well as to solve the safety problem.The simulation results show that the presented algorithm can achieve optimal attitude path and satisfy all constraints.
Purpose The purpose of this paper is to propose an attitude control algorithm for spacecraft with geometric constraints. Design/methodology/approach The geometric constraint is reformulated as a quadratic form when quaternion is used as attitude parameter, then the constraint is proved to be nonconvex and is further transformed to a convex one. By designing a new constraint formulation to satisfy the real constraint in the predictive horizon, the attitude control problem is reshaped to a convex planning problem which is based on receding horizon control. Findings The proposed algorithm is more effective in handling geometric constraints than previous research which used single step planning control. Practical implications With novel improvements to current methods for steering spacecraft from one attitude to another with geometric constraints, great attitude maneuver path can be achieved to protect instruments and meanwhile satisfy mission requirements. Originality/value The attitude control algorithm in this paper is designed especially for the satisfaction of geometric constraints in the process of attitude maneuver of spacecraft. By the application of this algorithm, the security of certain optical instruments, which is critical in an autonomous system, can be further assured.
Micro and nano technology is an indispensable part of modern science and technology. Because of the excellent advantages of high energy density, rapid response and large mechanical force, GMA becomes more promising in precision positioning, microelectronic, and biomedicine field[1], [2]. However, the relationship between input current and output displacement of GMA is hysteresis nonlinearity, which shows that the output of GMA not only relates to the current input value, but also relates to previous output value. Besides, the hysteresis nonlinearity is rate-dependent, so that the output of GMA depends on the input frequency. The intrinsic rate-dependent hysteresis nonlinearity of GMA is the main sticking point preventing its application in the high precision positioning [3], [4]. Therefore, modeling of GMA has long been difficult to study and attracted the attention of researchers. In this paper, the Prandtl-Ishlinskii (PI) model with the parameters self-tuning ability is established by the internal time-delay recurrent neural network (RNN) to describe the hysteresis nonlinearity of GMA. PI model consists of play operator and density function. Play operator is a continuous hysteresis operator, whose output depends on not only the current input but also the previous input. Nevertheless, play operator is rate-independent. Identifying the applicable density function is an important part of modeling PI model of GMA. Neural network has the features of the nonlinear mapping property and high parallel process ability. Therefore it is suitable to be applied to identify the nonlinear model. In this paper, the internal time-delay RNN is used to replace the density function of PI model. The PI model structure identified by the internal time-delay RNN for GMA is shown in Fig. 1. The internal time-delay RNN is set by the input layer, output layer and hidden layer. Where output of play operator $v_{i}(t)$ is the $i$ th input sample of the network at time $t$, $y^{\ast }(t)$ is the output of the network. $^{1}w_{ji}$ and $^{2}w_{j}$ are the weights of input layer and output layer, respectively, $^{h}w_{jk}$ is the weight for the nodes of hidden layer. Compared with feedforward neural network, it has property of memory because there is time delay recurrent existed in the hidden layer. Due to the inherent feedback structure of internal time-delay RNN, it possesses the dynamic characteristics and can adjust the parameters of PI model adaptively. The simulation results of PI model identified by internal time-delay RNN at the different input frequency are shown in Fig. 2. The red solid lines are hysteresis loops measured in the experiments, the blue dotted lines are the hysteresis loops of PI model based on internal time-delay RNN, and the blue solid lines are the modeling error curves. To facilitate simulation, the normalized data is adopted. As shown in Fig.2, the maximum modeling error rate at 1Hz, 10Hz, 50Hz and 100Hz is 0.81%, 1.07%, 1.41% and 2.14%, respectively. The PI model identified in this paper can accurately describe the hysteresis nonlinearity of GMA with the increase of input frequency. Therefore, the ability of precise modeling by PI model based on internal time-delay RNN is certified. The proposed PI model can be used to eliminate the hysteresis nonlinearity at the compensation control of GMA and promote the application of GMA in precision positioning field in the future.
During the deep space exploration, position determination is always very important for arriving at the target successfully. But only a little of navigation information can be used by the explorer after it is far away from the Earth. The autonomous navigation using asteroid sequence images provides a new way to solve the position estimation problem for deep space exploration. With more than ten asteroids' optical images, the spacecraft can determine its position autonomously after on-board image processing and computing. This paper focuses on the appropriate navigation asteroid selection and the maneuver sequence planning under the multi-constraints of optical sensors. A new synthesis selection criterion is proposed to evaluate the navigation value considering the influence of visible size, distance, relative velocity, line-of-sight angle and phase angle of asteroids. Based on the optimal performance-cost ratio asteroid set for this navigation, an improved maneuver sequence planning method using generic algorithm is proposed to realize the minimum photo-taking maneuver cost. At last, the simulation results show the advantages of this planning method.
With the rapid development of micro-nano manufacturing technology, there are more and more fields need nano-driven control technology, such as the high-precision positioning systems [1]. Magnetically controlled shape memory (MSM)-alloy actuators serve as the core part of high-precision positioning system on account of their high precision, large energy density, and small volume. The hysteresis nonlinearity of the MSM-alloy actuator, however, severely damages the positional accuracy of the positioning system. In order to research the hysteresis nonlinearity in the MSM-alloy actuator, hysteresis nonlinearity modeling has become a significant hot spot of research [2] [3]. The purpose of this study is to structure an excellent hysteresis nonlinearity model to capture the hysteresis nonlinearity in MSM-alloy actuators. The criterion for evaluating modeling performance is that the established hysteresis model can embody the actual characteristic of the actuator. In this study, a novel black-box model composed of the hysteresis-like structure and a nonlinear function is proposed to capture the hysteresis nonlinearity of the MSM-alloy actuator. The proposed black-box hysteresis nonlinearity modeling approach has the advantages of requiring no prior knowledge and internal physical mechanism. The hysteresis-like structure solves the multi-value mapping problem and accurately depicts the major and minor hysteresis loops of the MSM-alloy actuator. The nonlinear function represents the nonlinearity part of the MSM-alloy actuator, which is identified using least squares support vector machines (LS-SVM) on account of its strong approximation capability, high generalization ability, less parameters, and great computing power. The schematic diagram of black-box model is shown in Fig. 1. u(k) is the input current at k time, y(k) is the output displacement at k time, F[⋅] is the nonlinear function, H u [⋅] is the hysteresis-like part of the black-box model. In the procedure of modeling, u(k) and y(k) are the input values of hysteresis-like part; u(k), y(k), and H u [⋅] are the input values of nonlinear function, which is obtained by the LS-SVM. To certify the effectiveness of the black-box model, the simulations are implemented using the obtained experimental data. The simulations show that the modeling error rate of the novel black-box model based on the LS-SVM is 1.37%, which is improved 73.97% in compared with the results in [4]. It is obvious that the modeling precision of the proposed hysteresis model is within the allowable range. The simulation results are shown in Fig.2. The blue solid line is the obtained experimental data, and the red dotted line is the output of the proposed black-box model. As shown in Fig.2(a), the proposed black-box model based on the LS-SVM can accurately describe the major and minor hysteresis loops of the MSM-alloy actuator. The modeling error curve is shown in Fig.2(b). In the future, the proposed black-box model can lay a foundation for designing an adaptive controller to eliminate the hysteresis nonlinearity in the MSM-alloy actuator.
Direct detection laser detection and ranging (LADAR) has been widely used in many specific applications such as precision guidance, machine vision, underwater images, landslides investigations, city modeling, and so forth. One of the most promising methods to design, develop, test and validate a LADAR system is hardware-in-the-loop (HWIL) simulation. LADAR target simulator generates return signals of the simulated targets and background according to the test requirements. One of the key technologies of the LADAR target simulator is target modeling. A target modeling method based on data matching and restoring is pdroposed in this paper, which can provide a feasible way for LADAR target simulator to acquire the information of the target. The coordinate transformation is used to transform the target coordinate data under two or more viewpoint coordinate system into the reference point coordinate system to obtain the whole information of the target. Then, the target coordinate data under the reference coordinate system is transformed into a given viewpoint coordinate system. Furthermore, the deley time and the pulse width are calculated arrcording to a return signal mathematical model. Finally, the effects of the incident angle and target distance on target data are analyzed.
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