This paper contributes to the question of how to choose estimator memory length in system identification. Traditional approaches to this problem have been based on stationary models for parameter time variations. This...
This paper contributes to the question of how to choose estimator memory length in system identification. Traditional approaches to this problem have been based on stationary models for parameter time variations. This leads to a fixed trade-off between the “size” of parameter variations and the “size” of noise. However, in practice, one often experiences non-stationary parameter behaviour. The latter problem leads to the desirability of some form of time varying estimator memory. In particular, a short memory is desirable when rapid parameter changes occur. However, a long memory is desirable when infrequent parameters change occur so as to give maximal noise discrimination. The current paper discusses these issues at a conceptual rather than theoretical level. We illustrate the ideas by reference to parameter estimation in zinc galvanizing lines.
This paper investigates visual servoing stabilization of nonholonomic moving robots with unknown camera parameters. Based on the visual servoing feedback and the common chained form of type robot, we obtain a new kind...
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ISBN:
(纸本)9781424447749
This paper investigates visual servoing stabilization of nonholonomic moving robots with unknown camera parameters. Based on the visual servoing feedback and the common chained form of type robot, we obtain a new kind of uncertain model of nonholonomic kinemetic system firstly. Then a time varying feedback controller is proposed for exponentially stabilizing the position and orientation of the moving robot using visual feedback when the depth of the image features and the camera parameters are not known. This controller is developed based on a new formulation of the problem in the image space. The exponential stability of the closed loop system is rigorously proved. Simulation results demonstrate the effectiveness of the method proposed in this paper.
To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are *** calculating the whole damaging probab...
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To solve the weapon network system optimization problem against small raid objects with low attitude,the concept of direction probability and a new evaluation index system are *** calculating the whole damaging probability that changes with the defending angle,the efficiency of the whole weapon network system can be subtly *** such method,we can avoid the inconformity of the description obtained from the traditional index *** new indexes are also proposed,*** index,overlap index and cover index,which help manage the relationship among several *** normalizing the computation results with the Sigmoid function,the matching problem between the optimization algorithm and indexes is well ***,the algorithm of improved marriage in honey bees optimization that proposed in our previous work is applied to optimize the embattlement *** is carried out to show the efficiency of the proposed indexes and the optimization algorithm.
To resolve the problem of large angle and large scale image registration, an improved approach combining log-polar and SIFT is proposed. Firstly, the log-polar technique is implemented in order to achieve the prelimin...
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To resolve the problem of large angle and large scale image registration, an improved approach combining log-polar and SIFT is proposed. Firstly, the log-polar technique is implemented in order to achieve the preliminary registration result as well as estimate the arbitrary rotations parameters and large scale changes. Secondly, image is segmented into sub-blocks and six candidates of sub-blocks are extracted by information entropy, where SIFT features and moment features are fused to form a new feature descriptor. Finally, registration result is calculated by the matching points obtained by measuring the Euclidean distance. The experimental results show that the proposed algorithm is robust, fast with high-precision.
This paper proposes a class of H ∞ filter design for continue-time systems with time-varying delay. By using the convexity property of the matrix inequality, new criteria are derived for the H ∞ performance analys...
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This paper proposes a class of H ∞ filter design for continue-time systems with time-varying delay. By using the convexity property of the matrix inequality, new criteria are derived for the H ∞ performance analysis of the filtering-error systems, which can lead to much less conservative analysis results and thus reduce the overdesign of the filter. Finally, a numerical example is given to demonstrate the effectiveness and the merit of the proposed method.
Ground water level measurements are very important for a wide range of applications in geosciences, agriculture, environment monitoring and mining industry. Currently, reliable and automatic ground water level measure...
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Ground water level measurements are very important for a wide range of applications in geosciences, agriculture, environment monitoring and mining industry. Currently, reliable and automatic ground water level measurements have not been realized. This paper presents the simulation and design of a segmented resistance sensor for measuring ground water level. Based on this sensor design, we have developed an instrument that can automatically log the ground water level. Finite element simulations were performed to optimize the sensor design and to gain insight into its response. Experimental results in the lab and field have verified the usefulness of the sensor.
This paper deals with the robust iterative learning control(ILC) for time-delay systems(TDS) with both model and delay *** ILC algorithm with anticipation in time is considered,and a frequency-domain approach to its d...
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This paper deals with the robust iterative learning control(ILC) for time-delay systems(TDS) with both model and delay *** ILC algorithm with anticipation in time is considered,and a frequency-domain approach to its design is *** shows that a necessary and sufficient convergence condition can be provided in terms of three design parameters:the lead time,the learning gain,and the performance weighting *** particular,if the lead time is chosen as just the delay estimate,then the convergence condition is derived independent of the delay and the *** this case,with the selection of the performance weighting function,the perfect tracking can be achieved,or the least upper bound of the L2-norm of the limit tracking error can be guaranteed less than the least upper bound of the L2-norm of the initial tracking error.
Applying a novel nonlinear L2 gain control method for a doubly-fed induction motor (DFIM) based on port-controlled Hamiltonian (PCH) systems, A PCH model of DFIM was established. The desired closed-loop Hamiltonian fu...
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Applying a novel nonlinear L2 gain control method for a doubly-fed induction motor (DFIM) based on port-controlled Hamiltonian (PCH) systems, A PCH model of DFIM was established. The desired closed-loop Hamiltonian function was given. Against the load torque disturbance, L2 gain control law was designed in terms of PCH system and the L2 gain disturbances attenuation. The equilibrium stability of the system was also verified. Using SVPWM signal transformation method, speed regulation of non-salient pole SVPWM was implemented by controlling the switch point of every converter switch. The control of speed and electromagnetic-torque are tracking asymptotically when interferences exist in the surrounding environment. The simulation results show that the proposed scheme has a good performance.
This paper proposes a new type of regularization in the context of multi-class support vector machine for simultaneous classification and gene *** combining the huberized hinge loss function and the elastic net penalt...
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This paper proposes a new type of regularization in the context of multi-class support vector machine for simultaneous classification and gene *** combining the huberized hinge loss function and the elastic net penalty,the proposed support vector machine can do automatic gene selection and further encourage a grouping effect in the process of building classifiers,thus leading a sparse multi-classifiers with enhanced ***,a reasonable correlation between the two regularization parameters is proposed and an efficient solution path algorithm is *** of microarray classification are performed on the leukaemia data set to verify the obtained results.
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