Formation control from optimal control strategy is derived based on the position estimation for second-order molded agents using only the relative *** the proposed strategy,agents can realize the convergence to the de...
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ISBN:
(纸本)9781479947249
Formation control from optimal control strategy is derived based on the position estimation for second-order molded agents using only the relative *** the proposed strategy,agents can realize the convergence to the desired formation configure if and only if the interaction graph for the agents has a spanning *** control input is added into the derived control strategy,with the help of detecting obstacles using the relative position and taking avoidance measures using the estimated position,it can also realize obstacle avoidance for agents between themselves.
This paper studies the stability of state estimation for a discrete-time linear stochastic system, the states of which are measured by multiple sensors and transmitted over multiple wireless channels. Random packet lo...
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ISBN:
(纸本)9781479947249
This paper studies the stability of state estimation for a discrete-time linear stochastic system, the states of which are measured by multiple sensors and transmitted over multiple wireless channels. Random packet loss process introduced by each wireless channel is modeled by an independent and identically distributed(i.i.d.) Bernoulli process. The estimation strategy designed in this paper is based on Covariance Intersection fusion of local state estimates of the observable subsystem of each sensor. The sufficient conditions, imposing constraint on the packet success probability of each channel, are established by taking into account each observable subsystem structure to guarantee the expectation of the trace of estimation error covariance matrices is exponentially bounded, and the upper bound is given. Simulation examples are provided to demonstrate the effectiveness of the results.
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 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.
Wearable devices have appeared in every aspect of our lives, from small items such as wristbands and eyeglasses to finished garments as shoes and clothing. With the promoting of scientific development, intelligent tec...
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Wearable devices have appeared in every aspect of our lives, from small items such as wristbands and eyeglasses to finished garments as shoes and clothing. With the promoting of scientific development, intelligent technology is also combined with wearable devices to form a unique network that depends on the human body. The increasing demand for equipment has made smart wearable devices a research hotspot. Such equipment is usually small, light-weight, good flexibility, and can be adapted to the complex use of the environment. But these advantages just become the limitations of power supply for ***, the fixed charger can not be used to charge the device during use, and the volume of such a special battery can not be increased in order to increase the storage capacity. Therefore, how to solve the problem of power suppling for the wearable device effectively is a big challenge. Based on this, the paper proposes a distributed system of smart wearable energy harvesting, which considers the human body as the core and uses a variety of ubiquitous energy sources such as solar energy, thermal energy and mechanical energy. The system makes a combination of wearable and distributed design to form a wireless body area network,and provides a stable power output for smart wearable devices.
This paper is concerned with the distributed fusion estimation problem for linear system observed by multirate sensors in the environment of wireless sensor networks(WSNs). Rates of the sampling, estimation, transmiss...
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ISBN:
(纸本)9781467374439
This paper is concerned with the distributed fusion estimation problem for linear system observed by multirate sensors in the environment of wireless sensor networks(WSNs). Rates of the sampling, estimation, transmission in the WSNs are different. The distributed fusion estimation is composed of two stages. At the first stage, every sensor in the WSNs collects measurements of its own to generate a local estimation, then the local estimations from the neighboring sensors and the neighbour's neighbor sensors are further collected to form the fusion estimation at the second stage. The main result is that a distributed fusion estimation algorithm is presented which is simple and low energy consumption. The performance, namely, the effectiveness and the stability of the algorithm under multiple sensors, is analyzed. A numerical example is given to show the feasibility and effectiveness of the presented algorithm.
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.
Based on the comparison of several common methods of electronic compass error compensation, this paper presents a new error compensation method based on Adaptive Differential Evolution-Fourier Neural Networks (ADE-FNN...
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Based on the comparison of several common methods of electronic compass error compensation, this paper presents a new error compensation method based on Adaptive Differential Evolution-Fourier Neural Networks (ADE-FNN) to improve the measurement accuracy of electronic compass. This method uses Fourier neural network to model electronic compass error, and adopts Adaptive Differential Evolution to optimize the weights of neural network, and get more exact error model to compensate measured values. The compensation object is the common electronic compass composed by two-dimensional magnetic resistance sensor. Compared with the compensation effect of Least-square method, BP neural network and Fourier neural networks, It proves that the mode of this method can realize the high precision in the sample space mapping and high non-linear approximation ability, and this method has faster convergence rate, can avoid falling into local minima, reduces the training error, and improves error compensation accuracy. This method decreases the error range from -3.4° ~ 25.2° before compensation to -0.20° ~ 0.72°, and the average of the absolute error is 0.30°. Repeatability tests also proved the compensation plan have a good consistency.
This paper investigates the distributed tracking control problem for multiple Lagrangian systems under a general directed graph where only a portion of the agents have access to the desired time-varying trajectory. To...
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This paper investigates the distributed tracking control problem for multiple Lagrangian systems under a general directed graph where only a portion of the agents have access to the desired time-varying trajectory. To overcome the problem that only positions are measured, a observer is designed to estimate the velocity for each follower. By employing the estimated states, the distributed observer-based controller is proposed using only position measurements. Furthermore, the condition for the distributed tracking problem on the directed graph is derived, such that the tracking errors and observer errors semi-globally converge to zero. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.
In this paper,the adaptive robust control(ARC) algorithm is proposed for tracking control of the electric cylinder *** to the analysis of the working principle of the electric cylinder servo system,the model of the ...
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In this paper,the adaptive robust control(ARC) algorithm is proposed for tracking control of the electric cylinder *** to the analysis of the working principle of the electric cylinder servo system,the model of the system is established on the modified Lugre friction model,and single observer is designed for calculating friction as *** the ARC controller and adaptive law are designed for on-line parameters estimation,frictional compensation and the suppression external *** the Lyapunov approach,the stability of this system can be obtained in this *** simulation result shows that ARC can suppresses external disturbances effectively and realize real-time online parameter estimation.
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