In this study, a safe adaptive dynamic programming-based method is proposed for the formation control and collision avoidance problem of the multi-UAV systems with the known upper bound of external disturbances. For t...
In this study, a safe adaptive dynamic programming-based method is proposed for the formation control and collision avoidance problem of the multi-UAV systems with the known upper bound of external disturbances. For the position subsystem, an adaptive dynamic programming algorithm is established, using a designed cost function that manages to include uncertainty, tracking error, control influence, and barrier functions. Through the critic network structure with a unique weight learning criterion, the optimal cost function and control strategies are obtained. After attitude resolution, an integral back-stepping controller is established for the attitude subsystem. The simulation experiment is designed to verify the effectiveness of the algorithm.
Axisymmetric Vectoring Exhaust Nozzle (AVEN) of aero-engine undergoes deformation of its roller skeleton components due to thermal aerodynamic load, resulting in component jamming, increasing wear, and reducing lifesp...
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Currently, bearing fault signal diagnosis of mine drilling rig suffers from strong time dependency and serious signal noises, which leads to low diagnostic accuracy. Aiming at solving the problem of inadequate extract...
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To address the challenges of gesture recognition accuracy within human-computer interaction technologies, and to overcome the limitations of single-modal biometric feature recognition - which often falls short in prac...
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In this paper, the reliability test load spectrum of the aero-engine stator blade adjustment mechanism is studied. Based on the measured flight profile data of an aero-engine, the flight speed spectrum of the entire a...
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Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of o...
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Pattern synthesise of antenna arrays is usually complicated optimization problems,while evolutionary algorithms(EAs)are promising in solving these *** paper does not propose a new EA,but does construct a new form of optimization *** new optimization formulation has two differences from the common *** is the objective function is the field error between the desired and the designed,not the usual amplitude error between the desired and the *** difference is beneficial to decrease complexity in some *** second difference is that the design variables are changed as phases of desired radiation field within shaped-region,instead of excitation *** difference leads to the reduction of the number of design variables.A series of synthesis experiments including equally and unequally spaced linear arrays with different pattern shape requirements are applied,and the effectiveness and advantages of the proposed new optimization problems are *** results show that the proposing a new optimization formulation with less complexity is as significant as proposing a new algorithm.
This work analyzes the possibility of reducing the energy consumption of digital-to-analog converters by minimizing the energy consumption of the elements that ensure their operation. Due to the fact that such decisio...
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The structure of the variable stator vane (VSV) mechanism in aero-engines is complex. It is of great significance to investigate the dynamic response and force under aerodynamic loads and high-temperature conditions t...
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The rapid development of industrial automation makes the control process more and more demanding for the accuracy of system identification. Finding an effective identification model for regulating and controlling the ...
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We propose an online identification scheme for discrete-time piece-wise affine state-space models based on a system of adaptive algorithms running in two timescales. A stochastic approximation algorithm implements an ...
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ISBN:
(数字)9783907144107
ISBN:
(纸本)9798331540920
We propose an online identification scheme for discrete-time piece-wise affine state-space models based on a system of adaptive algorithms running in two timescales. A stochastic approximation algorithm implements an online deterministic annealing scheme at a slow timescale, estimating the partition of the augmented state-input space that defines the switching signal. At the same time, an adaptive identification algorithm, running at a higher timescale, updates the parameters of the local models based on the estimate of the switching signal. Identifiability conditions for the switched system are discussed and convergence results are given based on the theory of two-timescale stochastic approximation. In contrast to standard identification algorithms for piece-wise affine systems, the proposed approach progressively estimates the number of modes needed and is appropriate for online system identification using sequential data acquisition. This progressive nature of the algorithm improves computational efficiency and provides real-time control over the performance-complexity trade-off, desired in practical applications. Experimental results validate the efficacy of the proposed methodology.
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