In this paper,we consider the feedback stabilization problem of impulsive linear control systems with quantized input signals and quantized output *** concepts including quasi-invariant sets and attracting sets for hy...
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In this paper,we consider the feedback stabilization problem of impulsive linear control systems with quantized input signals and quantized output *** concepts including quasi-invariant sets and attracting sets for hybrid impulsive quantized systems are *** on these concepts and the analysis of related dynamic properties,we propose hybrid quantized control schemes to stabilize the considered impulsive systems via state and output feedback.
State observer design procedure is proposed for nonlinear locally Lipschitz systems. Possible presence of disturbances is taken into account. The solution is based on logic-based control approach applicable to nonline...
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State observer design procedure is proposed for nonlinear locally Lipschitz systems. Possible presence of disturbances is taken into account. The solution is based on logic-based control approach applicable to nonlinear systems with bounded solutions.
The use of the general controller synthesis setting for systems with active, or controlled, singularities under incomplete information and the single-impact and the multiimpact sequences given in [4] is illustrated by...
The use of the general controller synthesis setting for systems with active, or controlled, singularities under incomplete information and the single-impact and the multiimpact sequences given in [4] is illustrated by an optimal control law calculation for a ball/racket system.
This paper presents adaptive neural tracking control for a class of non-affine pure-feedback systems with multiple unknown state time-varying delays. The separation technique is introduced to decompose unknown functio...
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This paper presents adaptive neural tracking control for a class of non-affine pure-feedback systems with multiple unknown state time-varying delays. The separation technique is introduced to decompose unknown functions of all time-varying delayed states into a series of continuous functions of each delayed state. A novel Lyapunov-Krasovskii functional is employed to compensate for the unknown function of current delayed state, which is effectively free from any restrictive assumption on unknown time-delay functions. The proposed control scheme guarantees the boundedness of all the signals in the closed-loop system and the tracking *** studies are provided to demonstrate the effectiveness of the proposed scheme.
This paper considers the stabilization problem for a port-controlled Hamiltonian system subject to actuator saturation and input additive external disturbances. Conditions are identified under which a static output fe...
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ISBN:
(纸本)9781424445233
This paper considers the stabilization problem for a port-controlled Hamiltonian system subject to actuator saturation and input additive external disturbances. Conditions are identified under which a static output feedback law would achieve global asymptotic stabilization. Under some additional growth conditions on the nonlinear functions involved in the system, the same feedback law would also achieve finite gain L_(2) stabilization. In establishing these results, an estimate of the finite gain is also obtained.
A modified predictive optimal control (MPOC) scheme based on neural network modeling and particle swarm optimization (PSO) techniques is proposed in this paper for reheater steam temperature (RST) control of a large-s...
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A modified predictive optimal control (MPOC) scheme based on neural network modeling and particle swarm optimization (PSO) techniques is proposed in this paper for reheater steam temperature (RST) control of a large-scale boiler unit. A recurrent neural network is trained to directly model the temperature dynamic response of the reheater system. The neural network direct model is then used to evaluate the performance of the MPOC in search of the optimal control, where optimization is carried out with the PSO. A simplified PSO algorithm with search direction control is designed to find the nearest and optimal controls for the reheater steam temperature. To further improve the optimal search accuracy, each last-step prediction error between the direct model output and the actual RST is added to the current-step cost function to compensate for the model error. control tests on a full-scope simulator of a large scale power generating unit have shown the validity of the proposed method.
Rotary cement kiln is the main part of a cement plant that clinker is produced in it. Clinker is the main ingredient of cement. Continual and prolonged operation of rotary cement kiln is vital in cement factories. How...
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Rotary cement kiln is the main part of a cement plant that clinker is produced in it. Clinker is the main ingredient of cement. Continual and prolonged operation of rotary cement kiln is vital in cement factories. However, prolonged operation of the kiln is not possible and periodic repairs of the refractory lining would become necessary, due to non-linear phenomena existing in the kiln, such as sudden falls of coatings in the burning zone and probability of damages to the refractory materials during production. This is the basic reason behind the needs for a comprehensive model which is severely necessary for better control of this process. Such a model can be derived based on the mathematic analysis with consultation of expert operator experiences. In this paper both linear and nonlinear model are identified for rotary kiln of Saveh white cement factory. The linear model is introduced using Box-Jenkins structure. The results of the obtained model were satisfactory compared to some other linear models and can be used for designing adaptive or robust controllers. Also, nonlinear system identification via Neural Network technique is performed and its result was compared to linear models.
In this paper, control of parallel single-phase inverters in direct-quadrature(DQ) rotating frame based on droop method is proposed. For each inverter, a secondary orthogonal imaginary circuit is created to provide th...
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ISBN:
(纸本)9781424435067
In this paper, control of parallel single-phase inverters in direct-quadrature(DQ) rotating frame based on droop method is proposed. For each inverter, a secondary orthogonal imaginary circuit is created to provide the second phase required for the transformation; thus a DQ model of the inverter is obtained. The DQ transformation provides a time-invariant model of the inverter which makes the control design similar to that of dc-dc converters. The recognition of this analogy is important in that all of advanced dc-dc converters control techniques that have been previously developed can be applied to the control parallel inverters. The controller then is designed in DQ frame. Theoretically, infinite loop gain can be achieved in DQ rotating frame resulting in the elimination of the steady state error at the fundamental frequency of the inverter. The output impedance of the inverters is also considered, to ensure the decoupling between active and reactive power control using droop method. Simulation results are provided to prove the concept.
In this paper, authors are proposed drive system for BLDCM using motor drivers based on LabVIEW. Most researchers generally use Matlab/Simulink program as computer simulation tool for their control system design. Thes...
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ISBN:
(纸本)9781424424900
In this paper, authors are proposed drive system for BLDCM using motor drivers based on LabVIEW. Most researchers generally use Matlab/Simulink program as computer simulation tool for their control system design. These control system must be coded to the motor drivers using program language such as C for its verification. We developed drive system using LabVIEW, it is able to complete whole process from control system design to verification of control system without program coding. Authors also proposed power conversion stack designed for LabVIEW controller and BLDCM drive.
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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