In this paper, we propose a fast image/video dehazing algorithm based on modified atmospheric veil. For a single image, the coarse atmospheric veil is quickly estimated by the minimum and maximum channels. We take the...
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In this paper, we propose a fast image/video dehazing algorithm based on modified atmospheric veil. For a single image, the coarse atmospheric veil is quickly estimated by the minimum and maximum channels. We take the depth image estimated by the color attenuation prior as the guided image to refine the coarse atmospheric veil and use down sampling technique to speed up the process. In addition, a fast Fourier enhancement method is used to improve the high frequency details. Based on the image dehazing, we design an atmospheric light adjustment strategy and a transmission optimized framework for video dehazing, which can effectively reduce flickering artifacts. Experimental results demonstrate that the proposed algorithm can achieve a very good dehazing effect while keeping a comparable processing speed with state-of-the-art algorithms.
This paper aims to establish the simplest human walking model and provide a guide for controlling biped ***,a human motion capture system was utilized to sample the motion data of human walking and a representative su...
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This paper aims to establish the simplest human walking model and provide a guide for controlling biped ***,a human motion capture system was utilized to sample the motion data of human walking and a representative subject was ***,one of the simplest human walking model was set *** mechanical property analysis of human walking was done based on the established walking model via ***,the feasibility and effectiveness of proposed walking model were validated by numerical ***,the intrinsical relationships among human walking,biped walking model and control were discussed to provide a guide and insight for controlling biped robots.
As for a motion control framework of robots, virtual model control（VMC） can use virtual components to create virtual forces/torques. Actually, the virtual forces/torques are generated by joint actuators when the vir...
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As for a motion control framework of robots, virtual model control（VMC） can use virtual components to create virtual forces/torques. Actually, the virtual forces/torques are generated by joint actuators when the virtual components interact between robots and environments. In this paper, a virtual model control is proposed to do the dynamic balance control of quadruped robots in trot gait. In each leg, virtual model control includes swing phase control of robots and stance phase counterparts. In whole body, based on the forces/torques distribution method between two stance legs, virtual model control is mainly about the attitude control containing roll, pitch and yaw. Then, an intuitive approach of velocity control is employed for the locomotion of quadruped robots. Based on the velocity planning and control, a trajectory tracking control approach is investigated by considering four factors: terrain complexity index, curvature radius of given trajectory, distance to terminal, and maximum velocity of quadruped robots. Finally, the effectiveness of proposed controllers is validated by co-simulations.
Renewable energy sources, elastic loads, and purposeful manipulation of meter readings challenge the monitoring and control of today’s power systems (PS). In this context, fast and robust state estimation (SE) is tim...
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This paper considers the problem of stabilizing linear time-invariant systems with quantized state measurements under both external disturbances and Denial-of-Service (DoS) attacks. An element-based impulsive controll...
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ISBN:
(数字)9781728190938
ISBN:
(纸本)9781728190945
This paper considers the problem of stabilizing linear time-invariant systems with quantized state measurements under both external disturbances and Denial-of-Service (DoS) attacks. An element-based impulsive controller that can stabilize systems when quantization, DoS attacks and bounded disturbances coexist is proposed. A sufficient condition for stability characterized by the parameters of DoS attacks, bit-rate and the quantizer's saturation time is obtained. Moreover, analysis shows that under an appropriate design of parameters of the controller, the resultant saturation time always remains small. A numerical example is given to confirm the validity of the proposed method.
In this paper, we consider the plan recognition problem in the real-time strategy game. A probabilistic plan recognition algorithm is proposed to predict the future goals and identify the temporal logic tasks of the n...
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In this paper, we consider the plan recognition problem in the real-time strategy game. A probabilistic plan recognition algorithm is proposed to predict the future goals and identify the temporal logic tasks of the non-cooperative agent based on the observations. In order to model the temporal logic tasks, the plan library is composed of the Finite Transition system and Nondeterministic B ¨uchi automation. Specially, we provide a unified framework to combine the plan recognition and the planning, and propose the probability calculation algorithm to calculate the posterior probability distribution of the goals and tasks. Finally, we verify the effectiveness of the proposed algorithm by the compared simulations.
As a new emerging integrated navigation technology, the GNSS/INS/VO deep integration system can fully leverage the synergistic and complementary characteristics of the three involved subsystems to achieve cost reducti...
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Artificial pancreas (AP) systems are designed to automate glucose management for patients with type 1 diabetes. In this work, we propose an adaptive disturbance rejection control approach for AP systems to achieve saf...
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Artificial pancreas (AP) systems are designed to automate glucose management for patients with type 1 diabetes. In this work, we propose an adaptive disturbance rejection control approach for AP systems to achieve safe and effective glucose regulation. The controller is built within the framework of active disturbance rejection control, but incorporates safety operation constraints, and glucose- and velocity-dependent parameter adaptation modules for the keycontrol parameters. In silico performance comparison between the proposed controller and an adaptive zone model predictive controller (MPC) (Shi, Dassau, and Doyle III, 2019a) is conducted on the 10-adult cohort of the FDA-accepted UVA/Padova T1DM simulator. For both announced and unannounced meals, the controller achieves comparable glucose regulation performance in terms of mean glucose (134.9 mg/dL vs. 135.4 mg/dL, p < 0.001; 149.7 mg/dL vs. 151.7 mg/dL, p < 0.001, respectively) and percentage time in [70, 180] mg/dL (93.8% vs. 92.4%, p < 0.001; 76.0% vs. 72.4%, p < 0.001, respectively) without increasing the risk of hypoglycemia. The results indicate the feasibility of achieving comparable glucose regulation performance through a non-optimization control law for AP systems.
Due to the advantages of large unit capacity, high efficiency and high reliability, direct-drive permanent magnet synchronous generators (PMSGs) wind turbines (WTs) have been widely used in the offshore wind power gen...
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ISBN:
(数字)9781728133201
ISBN:
(纸本)9781728133218
Due to the advantages of large unit capacity, high efficiency and high reliability, direct-drive permanent magnet synchronous generators (PMSGs) wind turbines (WTs) have been widely used in the offshore wind power generation. The power loop controller aims to maintain the DC-Bus voltage of each PMSG-WT is equal to the others, guaranteeing that multiple WTs can be connected in DC serial parallel collection. In this paper, the DC-Port sequence impedance model of the PMSG-WT is established based on the harmonic linearization method, which takes the outer power loop into consideration. The impedance model is further verified by point-by-point scanning in MATLAB/Simulink. The proposed DC-Port impedance model of the PMSG-WT facilitates the establishment of offshore direct-drive wind farms, and is of great significance for analyzing and improving the system stability.
Phasor measurement units (PMUs) are vital for power grid monitoring, yet their high cost restricts widespread adoption. PMU measurement data is also crucial for fault analysis in power systems. However, existing resea...
Phasor measurement units (PMUs) are vital for power grid monitoring, yet their high cost restricts widespread adoption. PMU measurement data is also crucial for fault analysis in power systems. However, existing research seldom explores the interplay between optimal PMU placement (OPP) and fault analysis, impeding advancements in grid economy and security. This study introduces a perception-driven, deep learning-based optimization approach that integrates OPP, multi-task learning, and fault data augmentation. First, deep reinforcement learning optimizes PMU placement, balancing cost-effectiveness with observability requirements. Next, multi-task learning, enhanced by Bayesian optimization, improves fault classification efficiency using PMU data. Finally, pre-trained models paired with k -means clustering augment fault data, boosting classification accuracy. Extensive simulations across four IEEE standard test systems validate the proposed method’s effectiveness.
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