An adaptive switch gain time-varying sliding mode controller is designed for the low speed servo system in a control moment gyroscope (CMG). By introducing the integral of speed error in the sliding mode surface, the ...
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ISBN:
(纸本)9781479970995
An adaptive switch gain time-varying sliding mode controller is designed for the low speed servo system in a control moment gyroscope (CMG). By introducing the integral of speed error in the sliding mode surface, the error is suppressed during the whole operation. A time-varying sliding mode controller based on error reference is proposed to solve the problem that normal time-varying sliding mode control is only related to time and can only eliminate the reaching phase at initial time. The proposed controller makes the sliding mode surface keep refreshing all the time. The global robustness is maintained. Then, an adaptive switch gain sliding mode controller is proposed to deal with the system vibration. This controller has large gain for large error and small gain for small error. Simulation and experiment were carried out for the proposed CMG low speed servo system controller. The results showed that the proposed controller have better performance in terms of smooth speed and robustness comparing with conventional PID controller.
In this paper, we introduce a collaborative target tracking method which couples distributed estimation and motion control of mobile sensor networks. To estimate the target state, we develop a distributed federated fi...
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ISBN:
(纸本)9781479905607
In this paper, we introduce a collaborative target tracking method which couples distributed estimation and motion control of mobile sensor networks. To estimate the target state, we develop a distributed federated filter (DFF) approach where only local communication between sensors is required. This DFF algorithm has superiority in tolerance of the target system noise and can acquire accurate estimation even if the model of the target is not accurate. We value information-distribution and information-fusion weights in the DFF according to the measurement situations of sensors. Then a flocking-based motion control method is proposed to track maneuvering targets. During the process of tracking, velocity matching and collision avoidance among mobile sensors are guaranteed. Finally, this coupled estimation and control algorithm is successfully simulated to track a linear-dynamics target with non-zero acceleration. Simulation results verify the performance and superiority of our method.
In this paper, we focus on the need for autonomous vehicles' path planning and decision making in the urban environment. In our modified method, traffic lanes, road edge and geographic information system(GIS) are ...
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ISBN:
(纸本)9781467365970
In this paper, we focus on the need for autonomous vehicles' path planning and decision making in the urban environment. In our modified method, traffic lanes, road edge and geographic information system(GIS) are integrated to generate three structured road models, which can be used to reduce car's lateral positioning error and guarantee car's driving stably without a precise pre-computed map for localization. Based on these models, car's position, attitude and speed are taken into account to find an optimal guided path and a suitable behavior strategy to keep our car obeying traffic rules. Thus, in the whole architecture, the instability of some modules' detection results and low positioning accuracy of GPS receiver is resolved. Applied to our autonomous vehicle - IN 2 BOT, which has taken part in "Chinese intell.gent Vehicle Challenge" for many times, this method is proved more effective than our previous method after experiments under various conditions.
Accurate and robust power system state estimation (PSSE) is an essential prerequisite for reliable operation of smart power grids. In contrast to the commonly employed weighted least squares (WLS) one, the least-absol...
Accurate and robust power system state estimation (PSSE) is an essential prerequisite for reliable operation of smart power grids. In contrast to the commonly employed weighted least squares (WLS) one, the least-absolute-value (LAV) estimator is well documented for its robustness. Due to the non-convexity and non-smoothness however, existing LAV implementations are typically slow, thus inadequate for real-time system monitoring. In this context, this paper puts forward a novel LAV estimator leveraging recent algorithmic advances in composite optimization. Concretely, the estimator is based on a proximal linear procedure that deals with a sequence of convex quadratic problems, each efficiently solvable by means of either standard convex optimization methods, or the alternating direction method of multipliers. Simulated tests using two IEEE benchmark networks showcase its improved robustness and computational efficiency relative to several competing alternatives.
A new measuring system for magnetic properties of the ferromagnetic thin film has developed based on magneto-optical Kerr effect (MOKE). This system can realize both polar MOKE and longitudinal MOKE measurements throu...
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A new measuring system for magnetic properties of the ferromagnetic thin film has developed based on magneto-optical Kerr effect (MOKE). This system can realize both polar MOKE and longitudinal MOKE measurements through the optimization of optical path and electromagnet's poles. The signal processing software on lab View has been also designed to acquire the Kerr signal and plot the hysteresis loop. The MOKE measurements have been performed to investigate the magnetic properties of ferromagnetic films such as CoFeSiB, permalloy and NiFe/Ag/NiFe multilayer. The experimental results proved that the system has a high angular accuracy of 0.0008°.
Pedestrian detection plays an important role in the environmental perception and autonomous navigation for robotics, which provides critical information for the safe operation in complex environments. In this paper, a...
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