In this work, inspired from this biological motivation that in living cells, the execution time of different biological processes is difficult to know precisely and very sensitive to environmental factors that might b...
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This paper investigates the synchronization problem of memristive systems with multiple networked input and output delays via observer-based control. A memristive system is set up, and the fuzzy method has been employ...
This paper investigates the synchronization problem of memristive systems with multiple networked input and output delays via observer-based control. A memristive system is set up, and the fuzzy method has been employed to linearize the dynamical system of the memristive system; the networked input and output delays are considered in the synchronization problem of this system. A truncated predictor feedback approach is employed to design the observers. Under certain restrictions, a class of finite-dimensional observer-based output feedback controllers is designed. A numerical example is carried out to demonstrate the effectiveness of the proposed methods.
作者：
Li, JiaojieZhang, WeiSu, HoushengYang, YupuDepartment of Automation
Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Measurement and Control Technology
Shanghai Dian Ji University Shanghai China School of Automation
Key Laboratory of Image Information Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education National Key Laboratory of Science and Technology on Multispectral Information Processing Huazhong University of Science and Technology Wuhan China
In this paper, we study the flocking problem of multi-agent systems with obstacle avoidance, in the situation when only a fraction of the agents have information on the obstacles. Obstacles of arbitrary shape are allo...
In this paper, we study the flocking problem of multi-agent systems with obstacle avoidance, in the situation when only a fraction of the agents have information on the obstacles. Obstacles of arbitrary shape are allowed, no matter if their boundary is smooth or non-smooth, and no matter it they are convex or non-convex. A novel geometry representation rule is proposed to transfer obstacles to a dense obstacle-agents lattice structure. Non-convex regions of the obstacles are detected and supplemented using a geometric rule. The uninformed agents can detect a section of the obstacles boundary using only a range position sensor. We prove that with the proposed protocol, uninformed agents which maintain a joint path with any informed agent can avoid obstacles that move uniformly and assemble around a point along with the informed agents. Eventually all the assembled agents reach consensus on their velocity. In the entire flocking process, no distinct pair of agents collide with each other, nor collide with obstacles. The assembled agents are guaranteed not to be lost in any non-convex region of the obstacles within a distance constraint. Numerical simulations demonstrate the flocking algorithm with obstacle avoidance both in 2D and 3D space. The situation when every agent is informed is considered as a special case.
This paper is considered with the H ∞ observer design problem for a class of nonlinear systems with the one-sided Lipschitz condition. The systems under consideration include the well-studied Lipschitz system as a sp...
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This paper is considered with the H ∞ observer design problem for a class of nonlinear systems with the one-sided Lipschitz condition. The systems under consideration include the well-studied Lipschitz system as a special case and possess inherent advantages with respect to conservativeness. For such systems in the presence of noises, we develop a Linear Matrix Inequality (LMI) based approach to design a nonlinear H ∞ observer by carefully dealing with the one-sided Lipschitz condition together with the quadratic inner-bounded condition. The resulting nonlinear H ∞ observer guarantees asymptotic stability of the estimation error dynamics with a prescribed H ∞ performance. Moreover, for the design purpose, the existence condition of the proposed nonlinear H ∞ observer is formulated in terms of LMIs by using a matrix generalized inverse technique. Finally, a simulation example is given to illustrate the effectiveness of the proposed design.
This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Netw...
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This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Network (GA-BPNN). A case study of Yuhuangge landslide in the Three Gorges reservoir in China is used to illustrate the capability and merit of our schemes. In addition, the result shows that GP-BPNN get better accuracy than GA-RBFN in the same measurements.
This paper presents a new method to tune the parameters of the adaptation PI controller of full-order flux observer. The method employs an Immune Genetic Algorithm (IGA) based optimization routine that can be implemen...
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This work investigates the conflict-free path planning problems for efficient guidance of multiple mobile robots under the dynamic double-warehouse environment, a challenging problem that appears recurrently in a wide...
This work investigates the conflict-free path planning problems for efficient guidance of multiple mobile robots under the dynamic double-warehouse environment, a challenging problem that appears recurrently in a wide range of applications such as the service robots moving in a multistory building. United with two symmetrical transfer elevators, double-warehouse consists of two parallel warehouses. Within each warehouse, the polynomial based paths are subject to constraints such as motion boundaries, kinematics constraints, obstacle-avoidance, limited resource of elevators and smoothness. We formulate the shortest path planning problems as one time-varying nonlinear programming problem (TNLPP) while restricted to the above constraints, and apply the multi-phase strategy to reduce their difficulty. We present the new variant algorithms of PSO named constriction factor and random perturb PSO (Con-Per-PSO) and the simulating annealing PSO (SA-PSO) to achieve the solution. Numerical simulations verify that, our approach can fulfill multiple mobile robots path planning problems under double-warehouse successfully.
According to the distribution characteristics of the Pareto set (PS) of multi-objective optimization problems (MOPs), a cooperative coevolutionary model with new problem decomposition method was designed. By introduci...
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According to the distribution characteristics of the Pareto set (PS) of multi-objective optimization problems (MOPs), a cooperative coevolutionary model with new problem decomposition method was designed. By introducing the proposed coevolutionary model into artificial immune system, a cooperative immune coevolutionary algorithm for multi-objective optimization (CICAMO) was proposed. In CICAMO, the Tchebycheff decomposition method is employed to divide sub-populations at first, and then linear probabilistic models are built for each sub-population to piecewise approximate the distribution of the whole PS. In antibody reproducing step, two types of approaches based on clonal selection and model sampling are employed. Experimental results indicate that CICAMO can achieve a good performance in terms of both solution quality and convergence rate, especially when solving MOPs with non-linear relationship between decision variables.
In this paper, the formation tracking problem for the second-order multi-agent system with and without input delay are investigated, respectively. The objective is to design the formation tracking algorithm such that ...
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In this paper, the formation tracking problem for the second-order multi-agent system with and without input delay are investigated, respectively. The objective is to design the formation tracking algorithm such that a certain follower follows the trajectory of the leader while also maintains a certain desired geometric formation with other agents simultaneously. The impulsive algorithms are designed by using only the relative position information of the neighbors for both the cases with and without the input delay. By using properties of the Laplacian matrix and combining the stability theory of impulsive systems, necessary and sufficient conditions are derived to achieve the formation tracking of the second-order multi-agent system with and without the input delay, respectively. The numerical examples are given to illustrate the effectiveness of our theoretical results.
作者：
Jiao ShiJiaji WuXidian University
Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligent Information Processing Xi''an Shaanxi 710071China
The aurora is a natural light phenomenon in the sky, particularly in high-latitude *** is caused by the collision of energetic charged particles from the earth's magnetosphere and solar *** aurora is not only ...
The aurora is a natural light phenomenon in the sky, particularly in high-latitude *** is caused by the collision of energetic charged particles from the earth's magnetosphere and solar *** aurora is not only an optical *** also emits radio waves and has a strong influence on radio communications, on the weather, and on complex biological *** study of auroral activity attracts great interest form geophysicists due to its utility in analyzing high-latitude ionosphere-thermosphere-magnetosphere behaviors.A major source of images available for studying auroral activity consists of data collected by the Polar Ultraviolet imager (UVI).
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