In the highway environment, many applications require localization. It is common to use the Global Positioning System (GPS) to find the current position, but GPS is easily influenced by the external environment and ha...
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The paper considers nonlinear discrete-time repetitive processes using the state-space model setting. A form of passivity, termed G-passivity, is introduced and used, together with a vector storage function, to develo...
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The paper considers nonlinear discrete-time repetitive processes using the state-space model setting. A form of passivity, termed G-passivity, is introduced and used, together with a vector storage function, to develop a new design for output feedback based control to guarantee exponential stability of the controlled system. An extension to repetitive processes with possible failures, modeled by finite state Markov chain, is also given. Finally, these new results are applied to iterative learning control design in the presence of sensor failures.
The distributed networked control systems are considered in this paper. Several sub-systems which are connected with each other through a communication network make up the whole system. Each sub-system has its own qua...
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The distributed networked control systems are considered in this paper. Several sub-systems which are connected with each other through a communication network make up the whole system. Each sub-system has its own quantizer so that any information which needs be transmitted to other sub-systems will be quantized due to limited bandwidth. Meanwhile, the actuator faults, including outage, loss of effectiveness and stuck are also considered in our research. A mode-based state feedback controller is given in this paper to stable such NCSs and to meet the robust H-inf performance. A simulation example is proposed to illustrate the effectiveness of our method finally.
A substantial literature exists on the stability and control of 2D systems, including repetitive processes where iterative learning control algorithms designed in this setting have been experimentally verified. Most o...
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A substantial literature exists on the stability and control of 2D systems, including repetitive processes where iterative learning control algorithms designed in this setting have been experimentally verified. Most of this development has assumed that the dynamics can be adequately represented by linear state-space models, but applications exist where this assumption does not hold. This paper contributes to the development of a stability theory for nonlinear discrete-time 2D systems, where main results are on the use of vector Lyapunov functions to characterize exponential stability. The analysis includes systems where random failures modeled by a Markov chain with a finite set of states can arise in an iterative learning control application. An illustrative example is also given.
This paper proposes three dynamic voltage restorer (DVR) topologies. Such configurations are able to compensate voltage sags/swells in three-phase four-wire (3P4W) systems under balanced and unbalanced conditions. The...
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ISBN:
(纸本)9781479957774
This paper proposes three dynamic voltage restorer (DVR) topologies. Such configurations are able to compensate voltage sags/swells in three-phase four-wire (3P4W) systems under balanced and unbalanced conditions. The proposed systems in this work use two independent dc-links. The complete control system, including the PWM technique, is developed and comparisons between the proposed configurations and a conventional one are performed. Simulation and experimental results are provided to validate the theoretical approach.
In this work we deal with a system of autonomous mobile vehicles with limited communication range and consider the problem of the formally correct distributed control, i.e., the design of the local control for each pa...
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Repetitive processes are a class of two-dimensional systems that arise in the modeling of physical examples and also the control systems theory developed for them has, in the case of linear dynamics, been applied to d...
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Repetitive processes are a class of two-dimensional systems that arise in the modeling of physical examples and also the control systems theory developed for them has, in the case of linear dynamics, been applied to design iterative learning control laws with experimental verification. This paper gives new results on the stability of nonlinear differential repetitive processes for applications where a linearized model is either very limited or not applicable. The stability results are then applied to the design of iterative learning control laws in the presence of uncertain parameters and to the same problem when random failures occur that are modeled by a homogeneous Markov chain with a finite set of states. In both cases the computations required are expressed as a finite set of linear matrix inequalities.
The paper deals with the problem of automatic model selection of the nonlinear characteristic in a block-oriented dynamic system. We look for the parametric model of Hammerstein system nonlinearity. From the finite se...
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Model Checking is a method for verification. The model will be checked until the specification of it is proved or disproved. With the rising complexity of big models, there are non-checkable cases, in which cases the ...
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