Low-Cost Beam Steering that Covers the Entire Azimuthal Plane Powered by Amplitude-Only Synthesis of a Quintuple-Dipole Source

A new amplitude-only synthesis approach in quintuple electric dipoles(EDs)is proposed to enable the regulation of power flow in the azimuthal plane.The regulation methodology is investigated analytically with double ED,triple ED and quintuple ED models.First,when the phase difference between the EDs switches,the double ED model,acting as a reconfigurable source,can work in two modes with different power flow directions,i.e.,unidirectional mode and bidirectional mode.Then,from the triple ED model,it is verified that the power flow in the two working modes can be regulated to the desired direction in the azimuthal plane with high precision by controlling the feeding amplitudes of the dipoles.Moreover,a quintuple ED model is developed to enhance the symmetry and consistency of the power flow regulation in the plane.Finally,a prototype of the azimuthal beam steering system,including digitally controlled radio-frequency(RF)frontend tuning circuits,optimized practical feeding elements,and an end-fire radiator,is designed,fabricated and measured.Both unidirectional and bidirectional modes are observed,and satisfactory single-beam and dual-beam steering performance in the azimuthal plane is achieved.Unlike most phased arrays that realize beam steering by configuring phases,the beam steering of the proposed reconfigurable source in each mode can be arbitrarily synthesized only by the amplitudes of the quintuple feeding elements,which provides a new route for realizing low-cost and multifunctional beam-steering systems.

Control of Antagonistic McKibben Muscles via a Bio-inspired Approach

McKibben muscles are increasingly used in many robotic applications due to their advantages of lightweight,compliant,and skeletal muscles-like behaviours.However,there are still huge challenges in the motion control of McKibben muscles due to the system nonlinearity(e.g.,hysteresis)and model uncertainties.To investigate the control issues,a soft artificial arm actuated by an antagonistic pair of McKibben muscles,mimicking the biological structure of skeleton-muscle systems,is developed.Inspired by the biological motor control capability that humans can control and coordinate a group of muscles to achieve complex motions,a cerebellum-like controller based on Spiking Neural Networks(SNNs)is employed for the motion control of the developed artificial arm.Benefit from the employment of the SNN-based cerebellar model,the proposed control scheme provides online adaptive learning capability,good computational efficiency,fast response,and strong robustness.Finally,several simulations and experiments are conducted subject to different environmental disturbances.Both simulation and experimental results verify that the proposed method can achieve good tracking performance,adaptability,and strong robustness.