Velocity-Free MS/AE Source Location Method for Three-Dimensional Hole-Containing Structures

Microseismic/acoustic emission(MS/AE)source localization method is crucial for predicting and controlling of potentially dangerous sources of complex structures.However,the locating errors induced by both the irregular structure and pre-measured velocity are poorly understood in existing methods.To meet the high-accuracy locating requirements in complex three-dimensional hole-containing structures,a velocity-free MS/AE source location method is developed in this paper.It avoids manual repetitive training by using equidistant grid points to search the path,which introduces A*search algorithm and uses grid points to accommodate complex structures with irregular holes.It also takes advantage of the velocity-free source location method.To verify the validity of the proposed method,lead-breaking tests were performed on a cubic concrete test specimen with a size of 10 cm10 cm10 cm.It was cut out into a cylindrical empty space with a size of/6cm10 cm.Based on the arrivals,the classical Geiger method and the proposed method are used to locate lead-breaking sources.Results show that the locating error of the proposed method is 1.20 cm,which is less than 2.02 cm of the Geiger method.Hence,the proposed method can effectively locate sources in the complex three-dimensional structure with holes and achieve higher precision requirements.

Distributed velocity-free formation tracking control for clustered UAVs under virtual leader-follower framework

The collective formation control problem of a cluster of rotorcraft unmanned aerial vehicles(UAVs)is investigated in this article.The consensus tracking towards formation centroid with following UAVs forming a predefined configuration around the leader is considered as the objective.Unlike prior studies,the information of the central reference trajectory,which is deemed as a virtual leader in the leader-follower topology,is not directly accessible for partial nodes through the communication network.Therefore,a novel distributed formation tracking control scheme is promoted.Besides,a decentralized saturation observer is employed to estimate the reference acceleration signal of the virtual leader.In the absence of linear velocity measurement,two sliding manifolds are proposed by introducing the relative discrepancy terms of position and velocity.Then a smooth saturation operator in the form of a sigmoid function is applied to generate the command force input.Moreover,under the dilemma of constrained capabilities of the airborne sensors equipped on the rotorcrafts,the angular velocity is difficult to acquire.Two cascaded auxiliary attitude error systems are established on each rotorcraft system to synthesize the rotating torque with no need to require the angular velocity measurement.Due to the strong coupling and nonlinearity of the rotorcraft UAV system,the command angular velocity and the derivatives of command input are hard to obtain.Then a continuous nonlinear differentiator is proposed to work with the difficulties in deriving the explicit expression of system derivatives.Thereafter,a detailed stability analysis is conducted progressively on the angular control loop,reference trajectory observer loop,and the position control loop.A simulation scheme for a cluster of four rotorcraft UAVs tracking sinusoidal trajectory are presented and the formation control results are proven advantageous in comparison with the control protocol in previous literature.

Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the robot.The presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller design.The task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the inner-loop.Data-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance parameters.In the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity measurement.On this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task space.The simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.

Attitude Control of Rigid Body with Inertia Uncertainty and Saturation Input

In this paper, the attitude control problem of rigid body is addressed with considering inertia uncertainty,bounded time-varying disturbances, angular velocity-free measurement, and unknown non-symmetric saturation input. Using a mathematical transformation, the effects of bounded time-varying disturbances, uncertain inertia,and saturation input are combined as total disturbances. A novel finite-time observer is designed to estimate the unknown angular velocity and the total disturbances. For attitude control, an observer-based sliding-mode control protocol is proposed to force the system state convergence to the desired sliding-mode surface; the finite-time stability is guaranteed via Lyapunov theory analysis. Finally, a numerical simulation is presented to illustrate the effective performance of the proposed sliding-mode control protocol.