This paper is concerned with the identification problems of linear parameter varying (LPV) systems with randomly missing output data. Since one local linearized model cannot capture the global dynamics of the nonlinea...
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This paper is concerned with the identification problems of linear parameter varying (LPV) systems with randomly missing output data. Since one local linearized model cannot capture the global dynamics of the nonlinear industrial process, the multiple-model LPV model in which the global model is constructed by smoothly weighted combination of multiple local models is considered here. The problem of missing output variables data is commonly encountered in practice. In order to handle the multiple-model identification problems of LPV systems with incomplete data, the local model is taken to have a finite impulse response (FIR) model structure and the generalized expectation-maximization (EM) algorithm is adopted to estimate the unknown parameters of the global LPV model. To avoid the problems of ill-conditioned matrices and high sensitivity of parameters to noise, the prior information on the coefficients of each local FIR model is employed to construct the prior probability of unknown parameters. Then the maximum a posteriori (MAP) estimates of the global model parameters are derived via the generalized EM algorithm. The numerical example is presented to demonstrate the effectiveness of the proposed method.
In this paper, we present the theory of online sparse least squares support vector machine (OS-LSSVM) for prediction and propose a predictor with OS-LSSVM to detect sensor fault. The principle of the predictor and its...
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A biomimetic underwater vehicle propelled by two undulating long-fins is introduced in this paper. The concerned vehicle is propelled by two symmetrical undulating long-fins installed on both sides. Ten servo motors a...
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A biomimetic underwater vehicle propelled by two undulating long-fins is introduced in this paper. The concerned vehicle is propelled by two symmetrical undulating long-fins installed on both sides. Ten servo motors are employed to drive the long-fins and cosine wave function is employed for motor control. A real-time control system is designed for controlling the long-fins by adjusting its oscillating frequency and oscillating amplitude. An inertial measurement unit is installed to collect the accelerations and angular velocity. To obtain the relationship between oscillating frequency/amplitude and swimming performance, kinematic analysis and hydromechanic analysis are given. By dividing the long-fin into many small elements and computing the hydrodynamic force acting on each element, the instantaneous thrust generated by the long-fin is obtained. Then the average thrust of the long-fin is obtained by summing up the forces acted on the elements in one undulating period. Then swimming experiments are carried out to validate the vehicle design and kinematic analysis and hydromechanic analysis. And two swimming motion modes including marching and rotating locomotion are chosen. Finally, discussions between the swimming performance and the oscillating parameters are given.
The property of the soft magnetic composite (SMC) material is introduced. Take the traditional material used for electric machine, i.e. the silicon steel lamination, as the reference, this paper summarizes the applica...
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An overview of the modeling, optimization and control issues regarding digital ground-based weapon systems is provided by reviewing the previous works along five research lines: 1) design and optimization of the archi...
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A literature review regarding intelligent optimized control (IOC) is provided along the branches including fuzzy optimized control, neural optimized control, fuzzy-neural optimized control, intelligent optimizers base...
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This paper is concerned with the problem of data-driven predictive control for networked controlsystems (NCSs), which is designed by applying the subspace matrices technique, obtained directly from the input/output d...
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This paper is concerned with the problem of data-driven predictive control for networked controlsystems (NCSs), which is designed by applying the subspace matrices technique, obtained directly from the input/output data transferred from networks. The networked predictive control consists of the control prediction generator and network delay compensator. The control prediction generator provides a set of future control predictions to make the closed-loop system achieve the desired control performance and the network delay compensator eliminates the effects of the network transmission delay. The effectiveness and superiority of the proposed method is demonstrated in simulation as well as experiment study.
The information fusion of vision sensor and Millimeter Wave(MMW) radar can enhance the adaptability of the Unmanned Ground Vehicle(UGV) to the complex environment. Space alignment is the basic step of information fusi...
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The information fusion of vision sensor and Millimeter Wave(MMW) radar can enhance the adaptability of the Unmanned Ground Vehicle(UGV) to the complex environment. Space alignment is the basic step of information fusion. Based on the alignment problems camera and MMW radar has existed, firstly, according to the max velocity of UGV and the different attention on the close and far object, the calibration distance is determined and divided; then, a space alignment method is presented through the corresponding space point sets in image pixel coordinate of camera and polar coordinate of MMW radar. the results are verified through the experiment and the error is also analyzed.
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