This paper focuses on the optimal control of continuous-time linear time-varying uncertain systems with completely unknown internal dynamics and proposes a novel approach which leads to an optimal controller with guar...
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ISBN:
(纸本)9781509015740;9781509015733
This paper focuses on the optimal control of continuous-time linear time-varying uncertain systems with completely unknown internal dynamics and proposes a novel approach which leads to an optimal controller with guaranteed stability. A model-free algorithm of adaptive dynamic programming is employed to deal with the uncertainty of system parameters, yielding an optimal feedback controller for the system subject to a predefined cost. Then the stability of the system in time-varying uncertain situation which may undergo parameter changes or jumps is analyzed from the perspective of finite-time stability. On the basis of these results, a switching control strategy is presented to ensure the stability of the time-varying uncertain system with desired optimality properties in the long run. The effectiveness of the strategy is verified by simulations on a DC torque motor servo system.
Motion detection plays a crucial role in most video based applications.A particular background subtraction technique called ViBe(Visual Background Extractor) is commonly used to obtain foreground objects from the back...
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ISBN:
(纸本)9781509009107
Motion detection plays a crucial role in most video based applications.A particular background subtraction technique called ViBe(Visual Background Extractor) is commonly used to obtain foreground objects from the background due to its high detection rate and low computational ***,the performance is not very ***,this paper presents an improved ViBe algorithm to increase the accuracy and robustness of motion ***,a foreground feature map is created by optimizing the result of ViBe *** the edge detection of the original video frames is achieved after pre-sharpening using improved Sobel operator and Otsu ***,by feature fusion(of the foreground and background feature maps) and contour filling,the motion detection results can be *** experiments demonstrate the improvements of the proposed modifications at a limited additional cost.
To ensure that people can supplement enough water at the right time, an initiative service method based on intention understanding for drinking service robot is proposed. Firstly, individual factors and environmental ...
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To ensure that people can supplement enough water at the right time, an initiative service method based on intention understanding for drinking service robot is proposed. Firstly, individual factors and environmental factors which are associated with personal intentions are collected. Secondly, users' intention and desire degree for intention are obtained by an improved Fuzzy-Context-specific Intention Inference method. Then the relationship between personal intention and human demands is established by an initiative service model. Finally, robots provide drinking water service initiatively according to humans' demands. Drinking service experiments are performed in a laboratory scenario using a humans-robots interaction system. The experimental results show that the drinking time of actual situation lags behind the initiative service time 25 minutes on average, and the initiative service renders drinking service 2 times more than actual situation on average, which demonstrates the feasibility of the proposal. In prospect, the initiative service method could be applied to many occasions in our daily life, e.g., family service, caring for the elderly, and medical rehabilitation.
In this paper, the analysis of quantized effect on robust distributed consensus of linear uncertain multi-agent systems(MASs) via sliding-mode control(SMC) is investigated. Two kinds of phenomena on input quantization...
In this paper, the analysis of quantized effect on robust distributed consensus of linear uncertain multi-agent systems(MASs) via sliding-mode control(SMC) is investigated. Two kinds of phenomena on input quantization, including quantization mismatch and quantization measurement saturation, are analyzed. It shows that robust distributed consensus of linear uncertain MASs via SMC strategy might not be well achieved when the two kinds of quantization phenomena are ignored in the control design. Several research ideas for quantized feedback robust consensus via SMC strategy are finally discussed.
Optimal capacity planning and optimal production control are both very important to the improvement of the performance of a manufacturing system. However, in existing research and practice, the two problems are usuall...
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This paper investigates a data-based robust decentralized stabilizing control scheme for unknown large-scale systems via adaptive critic designs. The control consists of near-optimal stabilizing control and adaptive r...
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This paper investigates a data-based robust decentralized stabilizing control scheme for unknown large-scale systems via adaptive critic designs. The control consists of near-optimal stabilizing control and adaptive robustifying compensation. In order to avoid the common assumptions of boundedness and matched condition on interconnections, the actual states of interconnected subsystems are replaced with their desired ones. By using local input-output data, the subsystem dynamics can be obtained by neural network (NN) identifier. Then, with the help of local critic NN, the near-optimal decentralized control is derived via identifier-critic architecture for corresponding subsystems. Considering the replacement error, identification error and approximation error as overall error, an adaptive robustifying term is added to overcome it in real-time. Simulation example is given to verify the effectiveness of the present control scheme.
State estimation is a core objective in cyber-physical systems. In the state estimation problem over linear systems, the Kalman filter is the standard solution. The filter is the format on which the solutions to subse...
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ISBN:
(纸本)9781509045839
State estimation is a core objective in cyber-physical systems. In the state estimation problem over linear systems, the Kalman filter is the standard solution. The filter is the format on which the solutions to subsequent estimation problems are based. Among these problems are the estimation problem in the presence of packet drops and estimation problem involving event-based triggers. We study in this paper both phenomena simultaneously. In an attempt to find the Kalman-like filter, which proves the Gaussianity of the state and offers a set of update equations, our paper shows that no such filter exists. More precisely, one cannot find an event-based trigger such that under possible packet drops, the state variable remains a Gaussian variable. This conclusion can be reasonably extended to a more general setting.
This paper presents an Euler discretized inertial delayed neuron model, and its bifurcation dynamical behaviors are discussed. By using the associated characteristic model, center manifold theorem and the normal form ...
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This paper presents an Euler discretized inertial delayed neuron model, and its bifurcation dynamical behaviors are discussed. By using the associated characteristic model, center manifold theorem and the normal form method, it is shown that the model not only undergoes codimension one(flip, Neimark-Sacker) bifurcation, but also undergoes cusp and resonance bifurcation(1:1 and 1:2) of codimension two. Further, it is found that the parity of delay has some effect on bifurcation behaviors. Finally, some numerical simulations are given to support the analytic results and explore complex dynamics, such as periodic orbits near homoclinic orbits, quasiperiodic orbits, and chaotic orbits.
Three-phase inverter is a very important interface in microgrid. Droop control and virtual impedance are widely used to improve the power sharing capability and stability of such system, which however becomes ineffect...
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