Solving the explicit model predictive control (MPC) problem entails enumerating a list of critical regions and their ancillary feedback laws. Unfortunately, their number and the time required to compute them increase ...
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State observers for nonlinear systems are often designed for a canonical form of this system. However, this form may possess singular points, where the vector field is not defined or a Lipschitz condition is not fulfi...
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In this contribution we discuss the design of functional observers for polynomial systems. Our approach is based on a high gain design employing an embedded observer. The functional to be estimated is generated from t...
The persistence, bioaccumulation, and toxicity of perfluorinated and polyfluoroalkyl substances (PFASs), along with their concentrations in the environment and humans, have attracted global attention. However, so far,...
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When the aircraft is moving at high speed in the atmosphere,aero-optical imaging deviation will appear due to the influence of aero-optical *** order to achieve real-time compensation during the flight of the aircraft...
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When the aircraft is moving at high speed in the atmosphere,aero-optical imaging deviation will appear due to the influence of aero-optical *** order to achieve real-time compensation during the flight of the aircraft,it is necessary to analyze and predict the obtained imaging deviation *** order to improve the search speed and accuracy of the prediction algorithm and the ability to jump out of local optimum,in this paper,an improved sparrow search algorithm optimized extreme learning machine(ISSA-ELM) neural network model is proposed to predict the aero-optical imagine ***,the performance of ISSA-ELM,ELM neural network and SSA-ELM neural network was *** results showed that compared with ELM and SSA-ELM algorithms,the convergence speed of ISSA-ELM was significantly enhanced,and the accuracy of data prediction was also significantly improved.
This research suggests a methodology to optimize Elman neural network based on improved slime mould algorithm(ISMA) to anticipate the aero optical imaging *** improved Tent chaotic sequence is added to the SMA to init...
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This research suggests a methodology to optimize Elman neural network based on improved slime mould algorithm(ISMA) to anticipate the aero optical imaging *** improved Tent chaotic sequence is added to the SMA to initialize the population to accelerate the algorithm’s speed of ***,an improved random opposition-based learning was added to further enhance the algorithm’s performance in addressing problems that the SMA has such as weak convergence ability in the late iteration and an easy tendency to fall into local optimization in the optimization process when solving the optimization ***,the algorithm model is compared to the Elman neural network and the SMA optimization Elman neural network *** three models are assessed using four evaluation indicators,and the findings demonstrate that the ISMA optimization model can anticipate the aero optical imaging deviation in an accurate way.
The need for better search and rescue capabilities has led to the increased demand for collaborative aerial-ground multi-robot deployments. However, most existing solutions require high communication bandwidth or bulk...
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The need for better search and rescue capabilities has led to the increased demand for collaborative aerial-ground multi-robot deployments. However, most existing solutions require high communication bandwidth or bulky sensor equipment that is not suitable especially for aerial robots. To make the execution of these tasks more efficient, this paper proposes an angle-specified heterogeneous leader-follower formation framework consisting of unmanned aerial vehicles (UAVs) flying in a 3D space and ground robots moving in a 2D plane. The UAVs are controlled to maintain a desired angle-specified formation with the first three UAVs as the leaders forming a triangular shape and the remaining UAVs as the followers. The follower UAVs only need direction measurements to track the leader UAVs. For the ground robots, two leader robots track the UAV group and determine the orientation and scale of the ground formation, while the follower robots track the leader robots using only direction measurements. The proposed heterogeneous formation framework is energy-efficient as most robots only require low-cost and lightweight direction measurements. The stability of the proposed formation control algorithms is proved and validated through various physical application experiments. IEEE
This paper studies a dynamical system that models the free recall dynamics of working *** model is an attractor neural network with n modules,named hypercolumns,and each module consists of m *** mild conditions on the...
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This paper studies a dynamical system that models the free recall dynamics of working *** model is an attractor neural network with n modules,named hypercolumns,and each module consists of m *** mild conditions on the connection weights between minicolumns,the authors investigate the long-term evolution behavior of the model,namely the existence and stability of equilibria and limit *** authors also give a critical value in which Hopf bifurcation ***,the authors give a sufficient condition under which this model has a globally asymptotically stable equilibrium consisting of synchronized minicolumn states in each hypercolumn,which implies that in this case recalling is *** simulations are provided to illustrate the proposed theoretical ***,a numerical example the authors give suggests that patterns can be stored in not only equilibria and limit cycles,but also strange attractors(or chaos).
The Rural Hybrid Renewable Energy System (RHRES) holds great significance as a prospective energy system development. Ensuring its economic viability and low-carbon operation is crucial in order to fully harness its p...
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Due to the dispersed and disorderly feathers of distributed photovoltaic (PV) power generation on the user side, the difficulties of the low-carbon transformation of the power grid and sustainable development of large...
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