The force feedback technology has a crucial impact on the precise control of teleoperation system. Robots in fields such as minimally invasive surgery and nuclear waste cannot integrate force sensors to obtain force feedback due to their end size and harsh working environment. In order to obtain end-effector force feedback in sensorless situation, a sensorless force estimation model based on artificial neural network is defined in this paper. For improving the model prediction ability, a new Multi-layer Depth Extreme Learning Machine (MDELM) is proposed. Firstly, the network structure of the extreme learning machine is redesigned, and the smoothing function and Gauss-Laplacian function are constructed as the feature extraction layer and enhancement layer of the MDELM model. Then, to further improve the prediction performance of MDELM, an improved Sooty Tern Optimization Algorithm (STOA) is introduced to optimize the parameters of the model. The results show that the proposed force estimator outperforms the existing model with an MAE of less than 0.205, which is at least 18.65% lower than the existing model. In addition, when the acceleration of the remote operating system is a fixed constant or the information is not available,a sensorless force feedback system can be constructed by combining motor torque, joint position and joint velocity parameter. In general, this study provides an effective force estimation solution for teleoperation system without force sensor. 

Sensorless force estimation of teleoperation system based on multilayer depth Extreme Learning Machine

Imitating via manipulability: Geometry-aware combined DMP with via-point and speed adaptation

Achieving fast and stable synchronizer position tracking control can greatly improve the power and comfort of transmission shifting. In order to further improve the shift speed and stability of the synchronizer, this article takes the synchronizer control of a three-speed seamless transmission as the research object and proposes a variable impedance control method based on gain scheduling. Firstly, dynamic models of the shift actuator and synchronizer was established. Then, an impedance outer loop controller and a position inner loop controller were designed. In the impedance outer loop, adjust the synchronizer reference position based on the difference between the reference shift force and the actual shift force. At the same time, based on the actual control requirements of different motion stages of the synchronizer, the optimal impedance control parameters for each stage are selected for gain scheduling control. In the position inner loop, a prescribed performance-active disturbance rejection control is adopted, which solves the problem of system disturbance while ensuring the instantaneous performance of position tracking. Finally, simulations and bench tests were conducted on the position tracking control of synchronizer. The simulation and bench test results show that the control strategy proposed achieves fast and stable synchronizer position tracking, with superior control performance, which preliminarily verifies the effectiveness of the control strategy.

Variable impedance control for synchronizer position tracking based on gain scheduling

This paper proposes an adaptive admittance controller and a model-free non-singular fast terminal sliding mode controller based on an extended sliding mode observer for hybrid force and position control of a robotic arm driven by series elastic actuators (SEA) with external disturbances and model uncertainty. According to the ultra-local model method, simplifying the robotic arm driven by SEA dynamic model and all unknown terms which include the uncertainty of the model and unknown disturbance are integrated into one term called lumped total disturbance. In order to estimate the integrated unknown disturbance terms, an extended sliding mode observer (ESMO) is constructed. For better position control performance, a model-free non-singular fast terminal sliding mode controller was constructed by combining ultra-local model with non-singular fast terminal sliding mode control. In the outer loop, in order to accurately control the contact torque generated by interaction with the external environment in the hybrid force and position control of the robotic arm with changes in external environmental stiffness, an adaptive admittance controller is designed. To validate the effectiveness of the control strategy and the optimization effect on control performance, co-simulations of the SEA driven robotic arm are realized by using SolidWorks and MATLAB. Compare the co-simulation results with TDE-iPD to show the high accuracy and fast convergence characteristics of this control method.

Model-Free Non-Singular Fast Terminal Sliding Mode Controller Using Extended Sliding Mode Observer for Series Elastic Actuator-Based Robotic Arm

An adaptive bilateral impedance control based on nonlinear disturbance observer for different flexible targets grasping

This paper deals with the design, simulation and implementation of a digital signal processor (DSP)- based speed controller. The method applied is known as "integral variable structure model following control "(IVSMF)": which takes the error between the state of the model and the controlled plant, this error is to be minimized using the boundaries defined in the sliding mode plane. The control has been used to drive two types of permanent magnet motors, a PMDC motor and brushless AC motor, obtaining accurate speed regulation in both cases. The implementation is developed using two DSP's sharing a common memory, one is dedicated to implement the control algorithm and the other is devote to control the current controlled inverter (PWM), process the speed and current signals coming from the Hall effect current sensors and the position encoder. The control algorithm used is such if considers the variations from plant parameters, considering those parameters can have variations due to different factors such as core manufacture temperature, friction, etc. The results obtained show the robustness and the reliability of the controller when used with both the DC motor and the AC brushless motor.

DSP-based integral variable structure control for permanent magnet AC and DC motor drivers

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An adaptive bilateral impedance control based on nonlinear disturbance observer for different flexible targets grasping

DSP-based integral variable structure control for permanent magnet AC and DC motor drivers