Constructing topic hierarchies from the data automatically can help us better understand the contents and structure of information and benefit many applications in security informatics. The existing topic hierarchy co...
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ISBN:
(纸本)9781467384940
Constructing topic hierarchies from the data automatically can help us better understand the contents and structure of information and benefit many applications in security informatics. The existing topic hierarchy construction methods either need to specify the structure manually, or are not robust enough for sparse and noisy social media data such as microblog. In this paper, we propose an approach to automatically construct topic hierarchies from microblog data in a bottom up manner. We detect topics first and then build the topic structure based on a tree combination method. We conduct a preliminary empirical study based on the Weibo data. The experimental results show that the topic hierarchies generated by our method provide meaningful results.
Reinforcement learning has provided an efficient approach to solve the optimal control of some complicated systems. In this paper we resort to the idea of off-policy scheme and propose a complete-model-free algorithm ...
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ISBN:
(纸本)9781467371902
Reinforcement learning has provided an efficient approach to solve the optimal control of some complicated systems. In this paper we resort to the idea of off-policy scheme and propose a complete-model-free algorithm to the continuous-time nonlinear optimal control problems. The novel algorithm consists of two neural networks to approximate the value and policy and adapts them with continuous tuning laws. In addition, experience replay technique is employed so that both the instantaneous observations and the past data are utilized. The convergence to the optimal solutions are guaranteed under the Lyapunov analysis. A nonlinear system is simulated to test the learning performance.
Jellyfish-inspired jet propulsion and robotic implementation have drawn much attention among the scientific community. In this paper, we report a novel robotic jellyfish synthesizing mechanical structure drive and bar...
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ISBN:
(纸本)9781467396769
Jellyfish-inspired jet propulsion and robotic implementation have drawn much attention among the scientific community. In this paper, we report a novel robotic jellyfish synthesizing mechanical structure drive and barycenter adjustment mechanism. The robotic jellyfish relies on six-bar linkage mechanisms as actuators to realize the contraction-relaxation jet propulsion motion. To imitate the real jellyfish and to reduce drag, the robotic jellyfish is comprised of a streamlined head, a cavity shell, and a latex skin is enwraped around the drive units. To achieve free switch between different motion modes and transform attitude arbitrarily, a barycenter adjustment mechanism is embedded in the robot body. Through the upward, downward, balancing, as well as leaning-down motion of clump weights, the center of gravity of the robot can enwrap its center of buoyancy. Experimental tests on the actual robotic jellyfish verify the great 3D swimming ability.
In this paper, a novel robust adaptive control scheme is proposed for a lower limb rehabilitation robot designed by our laboratory. The proposed control strategy is based on the radial basis function (RBF) neural netw...
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ISBN:
(纸本)9781467396769
In this paper, a novel robust adaptive control scheme is proposed for a lower limb rehabilitation robot designed by our laboratory. The proposed control strategy is based on the radial basis function (RBF) neural networks and the parameters of the system dynamics are unknown. The weights of the RBF neural networks are updated by an adaptive law according to the Lyapunov stability analysis. The robustness against possible variations of the system dynamics and the external disturbance are considered in the control design. The proposed control strategy can not only avoid the complex procedure of system parameters identification, but also guarantee high robustness, small trajectory tracking errors and the assistance of the patient's voluntary participation. Using this control algorithm, the robot can regulate its exerted torque to adapt to the patient's active torque in real time during rehabilitation. The effectiveness of our control method is demonstrated by a simulation.
In this paper,we propose a time division multiple access(TDMA) based protocol that works on slightly modified IEEE 802.15.4 network in star topology for low latency deterministic networked control *** end device in ne...
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ISBN:
(纸本)9781479970186
In this paper,we propose a time division multiple access(TDMA) based protocol that works on slightly modified IEEE 802.15.4 network in star topology for low latency deterministic networked control *** end device in network transmits its data frame after certain time delay in response to periodic request from network *** time delay is optimized for channel bandwidth utilization and reliable data frame *** this TDMA based protocol eliminates the risk of frame collisions to great extent,MAC sub-layer modifications reduces the non-determinism of the network and increases its bandwidth *** were conducted to evaluate the suggested *** upon these experiments results,the proposed protocol is a feasible solution for controlsystems with real time constraints.
This paper aims at dynamic modeling and control of a new upper-limb rehabilitation robot which has a parallel structure. Dynamic modeling of parallel robot is a complicated problem, and the dynamics and voluntary forc...
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ISBN:
(纸本)9781479918096
This paper aims at dynamic modeling and control of a new upper-limb rehabilitation robot which has a parallel structure. Dynamic modeling of parallel robot is a complicated problem, and the dynamics and voluntary force of the patient arm increase the difficulty of dynamic analysis and control in rehabilitation training. The novelties of this study are: (1) dynamics of the robot and the patient are considered together, and this human-robot interaction system is modeled as a redundantly actuated closed-chain system (2 DOFs, 4 active joints); (2) the system dynamics are derived in workspace using a new method based on the dynamics of its three serial open-chain branches, and both kinematic constrains and interaction forces are considered during the derivation. Compared with the other two previous methods reviewed in this paper, the proposed method is easier to derive, more computationally efficient, and it can be used in both redundant and non-redundant cases. Besides, a model based PD-computed torque controller is designed and the simulation of passive training task along a circular path is presented to prove the effectiveness of this method.
Group consensus has both positive and negative communication weights, which is an extension to traditional consensus problem. Additionally, distributed event-triggered control has advantages over periodic control cons...
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Group consensus has both positive and negative communication weights, which is an extension to traditional consensus problem. Additionally, distributed event-triggered control has advantages over periodic control considering energy consumption and communication constraints. Thus, it is important to study group consensus using event-triggered control. Moreover, by calculating the maximum and minimum of the corresponding parameters, we can simplify the event-triggered function. The implementation will validate the effectiveness of our distributed control protocol.
This paper is concerned with adaptive filter and its application in SINS/GPS/DVS integrated navigation. A novel adaptive filter, namely, SH–STF, is presented by combining the Sage–Husa(SH) adaptive filter with the s...
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ISBN:
(纸本)9781467374439
This paper is concerned with adaptive filter and its application in SINS/GPS/DVS integrated navigation. A novel adaptive filter, namely, SH–STF, is presented by combining the Sage–Husa(SH) adaptive filter with the strong tracking filter(STF). For multirate sampling dynamic system and in consideration of observations randomly missing, SH–STF is applied to data fusion and SINS/GPS/DVS integrated navigation. Simulation results show the feasibility and effectiveness of the presented algorithm.
In this paper, we develop a novel approximate policy iteration reinforcement learning algorithm with unsupervised feature learning based on manifold regularization. The proposed algorithm can automatically learn data-...
In this paper, we develop a novel approximate policy iteration reinforcement learning algorithm with unsupervised feature learning based on manifold regularization. The proposed algorithm can automatically learn data-driven smooth basis representations for value function approximation, which can preserve the intrinsic geometry of the state space of Markov decision processes. Moreover, it can provide a direct basis extension for new samples in both policy learning and policy control processes. We evaluate the effectiveness and efficiency of the proposed algorithm on the inverted pendulum task. Simulation results show that this algorithm can learn smooth basis representations and excellent control policies.
This paper presents a novel jelly sh-inspired swimming robot whose mechanical design, control algorithm, and motion analysis are discussed and manifested in detail. In consideration of few research on robotic jelly sh...
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This paper presents a novel jelly sh-inspired swimming robot whose mechanical design, control algorithm, and motion analysis are discussed and manifested in detail. In consideration of few research on robotic jelly sh capable of threedimensional movement with mechanical drive and actuator, we propose an improved design mainly featuring six-bar linkage mechanisms as the actuators and a barycenter adjustment mechanism as an attitude regulator. To imitate the real jelly sh and to reduce drag, the robotic jelly sh is comprised of a streamlined head, a cavity shell, and an elastic rubber skin around the drive units. Meanwhile a bio-inspired central pattern generators control model is imported. To validate the feasibility of the maneuverability with designed motion mechanism and free attitude regulation, dynamic analysis and simulation experiment are conducted. The obtained results show the conceived novel robotic jelly sh can accomplish all motion tasks desired.
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