The stochastic resonance algorithm is widely used to process weak noisy signals with a single frequency. In practice, most signals are co-existing with multiple target frequencies, so stochastic resonance has certain ...
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With the development of urban rail transit and the installation of rigid catenary in low clearance tunnels during electrification renovations, the dynamic coupling of pantograph catenary in AC rigid contact network sy...
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The two-wheeled bicycle robot (TWBR) is a new intelligent transportation, which can be used for special tasks such as forest operation and disaster relief. Although the TWBR is not structurally complex, the dynamics a...
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Considering the characteristics of coordination among source-network-load-storage, a provincial local coordinated scheduling method based on the interaction of sourcenetwork-load-storage is proposed. Firstly, the inte...
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To address parameter uncertainty in the two-wheel balance vehicle (TWBV) system, a closed-loop subspace algorithm (CLSA) was employed to identify and correct uncertain structural parameters. This got in a more accurat...
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With the large-scale construction and the requirement of speed increase of high-speed railway in China, non-crossing crossover has been widely used in high-speed railway catenary. In order to satisfy the requirements ...
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Motor imagery has the advantages of non-invasiveness, safety and economic efficiency in post-stroke motor function rehabilitation, and has a wide application prospect in the field of medical rehabilitation. In this pa...
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The steady-state visual evoked potential (SSVEP) is one of the most commonly used paradigms in the BCI system, which produces a significant response to visual stimuli of a specific frequency. How to better improve the...
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This paper investigates the path-guided distributed formation control of networked autonomous surface vehicles(ASVs) subject to model uncertainties and environmental disturbances. A safety-certified path-guided coordi...
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This paper investigates the path-guided distributed formation control of networked autonomous surface vehicles(ASVs) subject to model uncertainties and environmental disturbances. A safety-certified path-guided coordinated control method is proposed for multiple ASVs to achieve a distributed formation in obstacle environments. Specifically, a neural predictor with a high-order tuner is presented to approximate unknown nonlinearities with accelerated learning performance. Subsequently, control Lyapunov functions(CLFs) and control barrier functions(CBFs) are constructed for mapping stability constraints and safety constraints on states to control inputs. A quadratic optimization problem is constructed with the norm of control inputs as the objective function, CLFs and CBFs as constraints. Neurodynamic optimization is used to deal with the quadratic programming problem and generate the optimal kinetic control signals, thereby attaining the desired safe formation. Unlike the high-order CBF, a CBF backstepping method is proposed to establish safety constraints such that repeated time derivatives of system nonlinearities can be avoided. The multi-ASVs system is ensured to be input-to-state safe irrespective of high-order relative degree. Through the Lyapunov theory, the multi-ASVs system is proven to be input-to-state stable. Finally, simulation results are presented to validate the efficacy of the presented safety-certified distributed formation control for networked ASVs.
In this paper, a motion control system has been designed. The system is used to control twelve motors which drive a parallel mechanism by adjusting pulse width modulation (PWM) with a microcontroller. The motors are s...
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