Traffic congestion leads to problems like delays, decreasing flow rate, and higher fuel consumption. Consequently, keeping traffic moving as efficiently as possible is not only important to economy but also important ...
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Traffic congestion leads to problems like delays, decreasing flow rate, and higher fuel consumption. Consequently, keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus, computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper, a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions.
The event-triggered H_(infinity) control design is investigated for networked controlsystems with uncertainties and transmission delays. A novel event-triggering scheme is proposed, which has some advantages over tra...
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ISBN:
(纸本)9781612848006
The event-triggered H_(infinity) control design is investigated for networked controlsystems with uncertainties and transmission delays. A novel event-triggering scheme is proposed, which has some advantages over traditional ones with a continuous detector. Considering the effect of the transmission delay, a delay system model for the analysis is firstly constructed. Then, based on the model and Lyapunov functional method, criteria for the stability with an H_(infinity) norm bound and criteria for the co-design of both the feedback gain and the trigger parameters are derived. In order to solve the feedback gain and the trigger parameters, the linear matrix inequality technique is employed. From the simulation example, it can be concluded that the proposed event-triggering scheme is superior to some other event-triggering schemes in some existing literature.
Most researches of traffic incident auto-detection are based on the data from fixed detectors, which are limited by costs and position. In order to resolve this problem, existing algorithms of traffic incident automat...
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Most researches of traffic incident auto-detection are based on the data from fixed detectors, which are limited by costs and position. In order to resolve this problem, existing algorithms of traffic incident automatic detection are analyzed and compared, and an algorithm of traffic incident auto-detection are provided based on mobile-detection technology. The traffic data are grouped in 5-min intervals, analyzed by a three-layer BP neural network, and utilized for traffic incident detection. 16 traffic incidents of different locations and different levels are modeled in the simulation experiment based on VISSIM, and detection rate, false alarm rate and average detection time are adopted as indicators to evaluate the algorithm. Finally, the algorithm is proved to be effective and applicable in practice.
A real time and autonomous obstacle avoidance method based on rules for mobile robots was presented. Wall- along algorithm was dynamically implemented in unknown environment without collision. The results show that th...
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A real time and autonomous obstacle avoidance method based on rules for mobile robots was presented. Wall- along algorithm was dynamically implemented in unknown environment without collision. The results show that this algorithm is time saving and no disturbance. The approaches proposed has effectiveness and reliability.
This paper presents an adaptive robust dynamic surface control (ARDSC) algorithm for the position control of DC torque motors which are modeled as third-order nonlinear systems with parametric and nonlinear uncertaint...
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The paper presents a target tracking algorithm which is based on the mean shift algorithm and the normalized moment of inertia (NMI) feature, because the result of the moving target tracking in the air is not satisfac...
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A variable structure neural network adaptive robust control (VSNNARC) is proposed for a class of uncertain nonlinear SISO systems. A neural network which is adjusted by using nodes activation and passivation technique...
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This paper presents an adaptive robust dynamic surface control (ARDSC) algorithm for the position control of DC torque motors which are modeled as third-order nonlinear systems with parametric and nonlinear uncertaint...
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ISBN:
(纸本)9781424474264
This paper presents an adaptive robust dynamic surface control (ARDSC) algorithm for the position control of DC torque motors which are modeled as third-order nonlinear systems with parametric and nonlinear uncertainties. Based on the dynamic surface control (DSC) approach, the "explosion of terms" problem in the normal adaptive robust control (ARC) is avoided, which enhances the practicability of the controller. Furthermore, besides theoretically proving that the tracking error is uniformly ultimate bounded or asymptotically converge to zero in presence of parametric uncertainties only, the true estimates of the unknown parameters are achieved by designing a novel adaptation law, which improves the system performance and can be used in system monitor and diagnosis on-line as byproducts. Finally, the comparative simulation results illustrate that the proposed algorithm is very effective.
Multi-targets video tracking theory is introduced briefly, and the structured Branching MHT algorithm is applied in Multi-targets video tracking system. Connected with Kalman filter, hypotheses are built by SB/MHT usi...
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ISBN:
(纸本)9787894631046
Multi-targets video tracking theory is introduced briefly, and the structured Branching MHT algorithm is applied in Multi-targets video tracking system. Connected with Kalman filter, hypotheses are built by SB/MHT using measures which are stretched by Bhattacharyya coefficient. In this way, Multi-targets video tracking can carry out. Feasibility of this method is validated by simulation.
This paper is devoted to robust adaptive sliding mode control for a class of nonlinear systems in the Takagi-Sugeno forms with mismatched parametric uncertainties. Sufficient conditions for the existence of linear sli...
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