In the nonlinear model predictive control (NMPC) field, it is well-known that the multistep control approach is superior to the single-step approach when examining high-order nonlinear systems. In the multistep contro...
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In the nonlinear model predictive control (NMPC) field, it is well-known that the multistep control approach is superior to the single-step approach when examining high-order nonlinear systems. In the multistep control approach, however, the online minimization of a 2-norm square objective function over a control horizon of length M always requires solving a set of complex polynomial equations, for which no definite solution exists so far. Moreover, the complex nature of the receding horizon optimization also causes additional problems to its closed-loop stability analysis. With these two serious challenges in mind, using a Volterra-Laguerre model-based NMPC for discussion, we propose a general technique to extend the control horizon with the assistance of Groebner basis, which transforms the set of complex polynomial equations to a much simpler form. We prove the closed-loop stability of the algorithm in the sense that the input and output series are both mean-square-bounded. Finally, the efficiency of this improved algorithm is examined on an industrial constant-pressure water supply system. Compared to the conventional NMPC schemes, the proposed method with the control horizon extension has shown a great potential to control a wide range of nonlinear dynamic systems.
In this paper, a specific feature analysis of liver ultrasound images including normal liver, liver cancer especially hepatocellular carcinoma (HCC) and other hepatopathy is discussed. According to the classification ...
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ISBN:
(纸本)9780819469533
In this paper, a specific feature analysis of liver ultrasound images including normal liver, liver cancer especially hepatocellular carcinoma (HCC) and other hepatopathy is discussed. According to the classification of hepatocellular carcinoma (HCC), primary carcinoma is divided into four types. 15 features from single gray-level statistic, gray-level co-occurrence matrix (GLCM), and gray-level run-length matrix (GLRLM) are extracted. Experiments for the discrimination of each type of HCC, normal liver, fatty liver, angioma and hepatic abscess have been conducted. Corresponding features to potentially discriminate them are found.
In this paper, a new genetic algorithm for solving multi-constrained optimization problems based on KS function is proposed. Firstly, utilizing the agglomeration features of KS function, all constraints of optimizatio...
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ISBN:
(纸本)9781424413393
In this paper, a new genetic algorithm for solving multi-constrained optimization problems based on KS function is proposed. Firstly, utilizing the agglomeration features of KS function, all constraints of optimization problems are agglomerated to only one constraint. Then, we use genetic aligorithm to solve the optimization problem after the compression of constraints. Finally, the simulation results on benchmark functions show the efficiency of our algorithm.
Gather the information of the environment by the monocular vision. Using the H and S weight of the HSV color model, separate the target from the environment with a certain color, by a fast clustering algorithm for two...
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ISBN:
(纸本)7900719229
Gather the information of the environment by the monocular vision. Using the H and S weight of the HSV color model, separate the target from the environment with a certain color, by a fast clustering algorithm for two-value image segmentation. Calculating the distance between the camera and target by the 3D reconstruction algorithm and sub-control strategy, and raise its veracity by laser information fusion. Furthermore, a vision servo system has been designed and utilized to achieve the robot's dynamic track. At last, some experiments were used to certification its availability.
With the extensive application of mobile robots in many different fields, map building in unknown environments has been one of the principal issues in the field of intelligent mobile robot. However, information acquir...
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ISBN:
(纸本)9780819469519
With the extensive application of mobile robots in many different fields, map building in unknown environments has been one of the principal issues in the field of intelligent mobile robot. However, information acquired in map building presents characteristics of uncertainty, imprecision and even high conflict, especially in the course of building grid map using sonar sensors. In this paper, we extended DSmT with Fuzzy theory by considering the different fuzzy T-norm operators (such as Algebraic Product operator, Bounded Product operator, Einstein Product operator and Default minimum operator)., in order to develop a more general and flexible combinational rule for more extensive application. At the same time, we apply fuzzy-extended DSmT to mobile robot map building with the help of new self-localization method based on delta neighboring field appearance matching(delta-NFAM), to make the new tool more robust in very complex environment. An experiment is conducted to reconstruct the map with the new tool in indoor environment, in order to compare their performances in map building with four T-norm operators, when Pioneer II mobile robot runs along the same trace. Finally, a conclusion is reached that this study develops a new idea to extend DSmT, also provides a new approach for autonomous navigation of mobile robot, and provides a human-computer interactive interface to manage and manipulate the robot remotely.
image fusion is an important tool in remote sensing, since many Earth observation satellites provide both high-resolution panchromatic (Pan) and low-resolution multispectral (MS) images. To date, many image fusion tec...
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ISBN:
(纸本)9780819469519
image fusion is an important tool in remote sensing, since many Earth observation satellites provide both high-resolution panchromatic (Pan) and low-resolution multispectral (MS) images. To date, many image fusion techniques have been developed. However, the available algorithms can hardly produce a satisfactory fusion result for IKONOS and QuickBird images. Among the existing fusion algorithms, the IHS technique is the most widely used one, and the wavelet fusion is the most frequently discussed one in recent publications because of its advantages over other fusion techniques. But the color distortion of these two techniques is often obvious. The support value fusion technique demonstrates some advantages over the conventional methods. This study presents a new fusion approach that integrates the advantages of both the IHS and the support value techniques to reduce the color distortion of QuickBird fusion results. Different QuickBird images have been fused with this new approach. Visual and statistical analyses prove that the concept of the proposed extended fast IHS (eFIHS) and support value integration is promising, and it does significantly improve the fusion quality compared to conventional IHS (eFIHS) and wavelet fusion techniques.
This paper introduces a new class of switching vector median filter. The proposed algorithm first uses four directional masks to analyze the color difference between the central pixel and its neighborhood pixels in th...
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ISBN:
(纸本)9780819469502
This paper introduces a new class of switching vector median filter. The proposed algorithm first uses four directional masks to analyze the color difference between the central pixel and its neighborhood pixels in the RGB color space and classify each color pixel into noisy pixel or noise-free one, and then employs the standard vector median filtering operations in the detected noisy locations to restore the corrupted pixels and leave the noise-free ones unchanged. The simulation results show that the proposed method excellently suppresses impulsive noise as well as preserving the image details well, and significantly outperforms the existing vector filtering solutions in terms of both the objective measures and the perceptual visual quality.
In this paper, we present some results on the bounded-input bounded-output (BIBO) stability of two-dimensional (2-D) recursive bilinear systems. Sufficient conditions are derived, which enable us to define a subset to...
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ISBN:
(纸本)9781424407361
In this paper, we present some results on the bounded-input bounded-output (BIBO) stability of two-dimensional (2-D) recursive bilinear systems. Sufficient conditions are derived, which enable us to define a subset to which system input signals should be confined so that the system output is bounded by a constant related to the system initial values and coefficients. Simple examples are presented to illustrate the results.
In this paper trajectory tracking control of a human arm moving in sagittal plane is investigated. The arm is described by a musculoskeletal model with two degrees of freedom and six muscles, and the control signal is...
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ISBN:
(纸本)9783540745808
In this paper trajectory tracking control of a human arm moving in sagittal plane is investigated. The arm is described by a musculoskeletal model with two degrees of freedom and six muscles, and the control signal is applied directly in muscle space. To design the intelligentcontroller, an evolutionary diagonal recurrent neural network (EDRNN) is integrated with proper performance indices, which a genetic algorithm (GA) and evolutionary program (EP) strategy are effectively combined with the diagonal neural network (DRNN). The hybrid GA with EP strategy is applied to optimize the DRNN structure and a dynamic back-propagation algorithm (DBP) is used for training the network weights. The effectiveness of the control scheme is demonstrated through a simulated case study.
Gather the information of the environment by the monocular vision. Using the H and S weight of the HSV color model, separate the target from the environment with a certain color, by a fast clustering algorithm for two...
详细信息
ISBN:
(纸本)9787811240559
Gather the information of the environment by the monocular vision. Using the H and S weight of the HSV color model, separate the target from the environment with a certain color, by a fast clustering algorithm for two-value image segmentation. Calculating the distance between the camera and target by the 3D reconstruction algorithm and sub-control strategy, and raise its veracity by laser information fusion. Furthermore, a vision servo system has been designed and utilized to achieve the robot's dynamic track. At last, some experiments were used to certification its availability.
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