In this study, the lth order (l≥2) consensus problem for multi-agent systems is considered, which generalises the existing second-order consensus algorithm. A linear consensus protocol is proposed for solving such a ...
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Specific index-related process monitoring covers a wide range of requirements from industrial production. At present, it is still a challenge to divide into the specific index-related information and the specific inde...
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Dynamic multi-objective optimization is a complex and difficult research topic of process systems engineering. In this paper, a modified Bare-bones MOPSO algorithm is proposed that takes advantage of few parameters of...
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Dynamic multi-objective optimization is a complex and difficult research topic of process systems engineering. In this paper, a modified Bare-bones MOPSO algorithm is proposed that takes advantage of few parameters of bare-bones algorithm. To avoid premature convergence, Gaussian mutation is introduced;and an adaptive sampling distribution strategy is also used to improve the exploratory capability. Moreover, a circular crowded sorting approach is adopted to improve the uniformity of the population distribution. Finally, by combining the algorithm with control vector parameterization, an approach is proposed to solve the dynamic optimization problems of chemicalprocesses. It is proved that the new algorithm performs better compared with other classic multi-objective optimization algorithms through the results of solving three dynamic optimization problems.
The collective behavior of certain animals and insects has the characteristic of self-organization. The simple interactions among individuals can produce complex adaptive patterns at the level of the group. Recently, ...
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The collective behavior of certain animals and insects has the characteristic of self-organization. The simple interactions among individuals can produce complex adaptive patterns at the level of the group. Recently, new scientific investigation pointed out that desert locusts show extreme phenotypic plasticity in transforming between the lonely phase and the swarming gregarious phase depending on the population density, which is controlled by a serotonin called 5-hydroxytryptamine. In this paper, based on the mechanism of the locusts' collective behavior, a new particle swarm optimization technique called LBPSO is studied. The number of swarms is self-adaptively adjusted by the acquired outstanding particles coming from behind the previous global best solution. The swarm sizes are related to the corresponding serotonin 5-hydroxytryptamine which is determined by the optimization parameters such as global best, iteration number etc. And each swarm adopts one of three rules below according to its density, generalized social evolution strategy, generalized cognition evolution strategy and the independent moving strategy. A comparative study of LBPSO, SPSO, Improved SPSO and the original PSO on their ability of tracking optima is carried out. And the results under four static benchmark functions and a dynamic function generator MPB show that LBPSO outperforms the other three functions in both static and dynamic landscapes due to the introduced locusts' collective behavior.
Brain computer interface (BCI) could help patients to manipulate external devices based on the specific brain activities. One of the most popular BCI systems is the visual-based BCI system. Mostly, users were asked to...
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In this paper, a quantized H∞ control problem for networked control systems (NCSs) subject to randomly multi-step transmission delays is investigated. A quantizer is used before the measurement signal enters the comm...
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作者:
Kosarnovsky, B.Arogeti, S.Ministry of Education
Key Laboratory of Advanced Control and Optimization for Chemical Processes (East China University of Science and Technology) Shanghai P. R. China
In this paper we present a novel concept of a tethered-drones system. The system includes an arbitrary number of drones connected serially to an active ground station. The considered drones are of quadrotor type. Util...
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ISBN:
(纸本)9781728136059
In this paper we present a novel concept of a tethered-drones system. The system includes an arbitrary number of drones connected serially to an active ground station. The considered drones are of quadrotor type. Utilizing a unique pulley-gimbal mechanism, each drone can freely move along the tether and its position is measured with respect to the ground station without the use of standard onboard inertial sensors. The proposed system can be thought of as a robotic arm where each tether section acts as a variable-length link and each drone is a joint actuator. We model the coupled behavior of the ground station and the string, taking into account an arbitrary number of drones. Then, a controller that combines tools from geometric-control and linear-control is suggested. Finally, the concept is demonstrated using numerical simulations, which also illustrate its potential effectiveness.
This paper investigates the problem of event-triggered dual-mode distributed predictive control(DPC) for constrained large-scale linear systems subject to bounded *** on input-to-state stability(ISS) theory,the event-...
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ISBN:
(纸本)9781509009107
This paper investigates the problem of event-triggered dual-mode distributed predictive control(DPC) for constrained large-scale linear systems subject to bounded *** on input-to-state stability(ISS) theory,the event-triggering condition involving information of the subsystem itself is derived.A dual-mode predictive control scheme is designed to reduce information exchanges with neighboring *** upper bound of disturbances for ensuring the recursive feasibility and closed-loop stability are ***,a simulation example is given to show that the presented method is able to save computation resources and communication resources while guaranteeing the desired control performance.
The flow shop scheduling problems with zero wait is considered as one of the most challenging problems in the field of scheduling. This paper deals with the problem considering the makespan minimization as the objecti...
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Nodes localization plays an important role in applications of wireless sensor networks. In this paper, a localization scheme with a mobile anchor using a hybrid algorithm (ABC-GA) which combines artificial bee colony ...
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Nodes localization plays an important role in applications of wireless sensor networks. In this paper, a localization scheme with a mobile anchor using a hybrid algorithm (ABC-GA) which combines artificial bee colony (ABC) algorithm with the advantages of genetic algorithm (GA) is proposed. The localization scheme determines location of unknown node by the mobile anchor;it has high accuracy without any additional requirements for the hardware of unknown node. The core problem of the scheme is finding the shortest path to traversal all unknown nodes. We use ABC-GA hybrid algorithm to solve this problem. Simulation results show that ABC-GA hybrid algorithm has high convergence rate and strong global search capability and the accuracy of localization scheme is satisfactory.
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