Manipulator Trajectory Tracking with a Neural Network Adaptive Control Method

In order to solve the joint chattering problem of the manipulator in the process of motion, a novel dynamics model is established based on the dynamics model of the manipulator, by fitting parameters of the neural network and combining with the estimated value of the inertia matrix. We proposed a neural network adaptive control method with a time-varying constraint state based on the dynamics model of estimation. We design the control law, establish the Lyapunov function equation and the asymmetric term, and derive the convergence of the control law. According to the joint state tracking results of the manipulator, the angular displacement, angular velocity, angular acceleration, input torque, and disturbance fitting of the manipulator are analyzed by using the Simulink and Gazebo. The simulation results show that the proposed method can effectively suppress the chattering amplitude under the environment disturbances.

Effects of different friction coefficients on input torque distribution in the bolt tightening process based on the energy method

Bolted joints are one of the most common fastening methods in engineering applications. To meet the requirements of structural parts, the torque method is often used for controlling the bolted joint performance. However, only a few investigations have been carried out on the conversion efficiency of bolt torque to the tensile force, leading to uncertainty and potential safety hazards during the bolt tightening. In order to study the input torque distribution and overcome problems caused by the Motosh method and experimental investigations, a new energy-based torque distribution model is established in the present study. In the proposed model, numerous affecting parameters, including the effective bearing radius, effective thread contact radius, spiral angle, and connector deformation are considered. Then a parameterized thread mesh model using finite element technology is proposed to analyze the influence of different bolt friction coefficients on the bolt tightening process. Based on 16 types of tightening analyses, it is concluded that as bolt friction coefficient increases, the corresponding torque conversion rate decreases from 14.45% to 7.89%. Compared with the Motosh method, the torque conversion rate obtained by the proposed method is relatively large, which makes the actual pre-tightening force larger than the design value. However, there is still a possibility of bolt failure.

Design of torque-compensated mechanical systems with two connected identical slider-crank mechanisms

Balancing the torque of mechanisms designed to minimize the fluctuation of input shaft torque is an effective means of improving their dynamic performance. There are several ways of solving the problem: optimizing the distribution of the moving mass of the original mechanism; cam sub-systems that displace the balancing mass; cam-spring mechanisms; flywheels driven by non-circular gears; adding articulated dyads, linkages or redundant drivers. This paper addresses the problem of input torque compensation with the optimal connection of two identical slider-crank mechanisms. The acceleration and deceleration phases of the links of the slide-crank mechanism obviously change periodically, causing torque to fluctuate at the input shaft. This is done by minimizing the root-mean-square value of the input torque of the combined linkages. Two schemes are considered: slider-crank mechanisms with sliders moving on the same side, and on opposite sides. The prime value of this study is that it proposes an analytically tractable solution for identifying the general dynamic properties of mechanisms. Based on the ratio of link lengths, the precise relations for optimal connection of identical slider-crank mechanisms, i.e. a connection that produces the minimum root-mean-square values of the input torque, are developed. The numerical simulations illustrate the efficiency of the suggested approach. Observations show that the best solutions from the point of view of input torque minimization are obtained for the value of the coupling angle of two mechanisms around 90°.

Input Torque Measurements for Wind Turbine Gearboxes Using Fiber Optical Strain Sensors

Accurate knowledge of the input torque in wind turbine gearboxes is key to improving their reliability. Traditionally, rotor torque is measured using strain gauges bonded to the shaft. Transferring the resulting signal from the rotating shaft to a stationary data acquisition system while powering the sensing devices is complex and costly. The magnitude of the torques involved in wind turbine gearboxes and the high stiffness of the input shaft pose additional difficulties. This paper presents a new alternative method to measure the input torque in wind turbine gearboxes based on deformation measurements of the static first stage ring gear. We have measured deformation using fiber optic strain sensors based on fiber Bragg gratings because of their advantages compared to conventional electrical strain gauges. The present study was conducted on a Siemens Gamesa Renewable Energy gearbox with a rated power of 6MW, in which a total of 54 fiber optic strain sensors were installed on the outer surface of the first stage ring gear. The gear mesh forces between the planets and the ring gear cause measurable deformations on the outer surface of the stationary ring gear. The measured strains exhibit a dynamic behavior. The strain values change depending on the relative position of the strain sensors to the planet gears, the instantaneous variations of the input torque, and the way load is shared between planets. A satisfactory correlation has been found between the strain signals measured on the static ring gear and torque. Two signal processing strategies are presented in this paper. The first procedure is based on the peak-to-peak strain values computed for the gear mesh events, and therefore, torque can only be estimated when a gear mesh event is detected. The second signal processing procedure combines the strain signals from different sensors using a Coleman coordinate transformation and tracks the magnitude of the fifth harmonic component. With this second procedure, it is possible to estimate torque whenever strain data of all sensors is available, leading to an improved frequency resolution up to the sampling frequency used to acquire strain data. The method presented in this paper could make measuring gearbox torque more cost-effective, which would facilitate its adoption in serial wind turbines and enable novel data-driven control strategies, as well as a more accurate assessment of the consumed fatigue life of the gearboxes throughout their operation.

Iterative Sliding Mode and Increment Feedback Attitude Control for On-Orbit Capturing Process of Spacecraft

According to the characteristics of spacecraft capturing noncooperative targets in orbit, an increment feedback controller based on nonlinear iterative sliding mode is presented. Firstly, the attitude tracking error equation is established, and then, an increment feedback control law based on bounded iterative sliding modes is proposed, which does not need to estimate the uncertain moment of inertia and external disturbances. For comparing, an adaptive sliding mode controller has been designed in the paper. Some numerical simulations have been given in the presence of spacecraft on-orbit capturing noncooperative target, and the simulation results show that the increment feedback controller has strong robustness to the unknown parametric variations and external disturbances and has a smaller control input torque in control process.

Performance Analysis of Different Techniques for Low Torque Ripple PMSM Drive using DTC

Permanent Magnet Synchronous Motors (PMSM) have demonstrated their usability in automotive and other files in the recent years. A low torque ripple PMSM drive proves to be suitable for power steering and hybrid vehicle applications. This paper presents analysis of two different techniques for low torque ripple PMSM drive using DTC and performs a comparative analysis of the ripples. The complete PMSM drives are modeled using MatLab Simulink environment where different blocks are interconnected to form the complete test setup. Input torque is applied to check the parameters of the drive including the ripples. Analysis shows that the technique Dual Inverter gives 6.442% of ripples whereas the SVPWM technique affects the output in terms of ripples by 0.9762%. The theoretical analyses and simulation results indicates that SVPWM technique can reduce the flux linkage and torque ripple in a large extent and have a better dynamic and static performance as compare to dual inverter technique

Bioinspired Monolithically Designed Compliant Swimming Robots

As technology advances and enables us to design and realize complex systems using new materials and manufacturing methods, biologically inspired robots in every aspect of engineering have attracted much attention in the last few decades. This paper presents the design and motion analysis of monolithically designed two compliant swimming robots that are actuated and controlled by single motor. Each design incorporates large deflecting compliant members and rigid levers to transfer the input torque to the different parts on the mechanism. While the first design integrates flexible tail to perform swimming motion, the second design adopts snapping type motion for the same action. Both mechanisms are 3D printed and tested for forward motion. The first robot has a constant speed of 0.68 BL/s while the second has an average speed of 0.6 BL/s. Kinematic model using pseudo rigid body modeling (PRBM) is derived to calculate the load-deflection curves of the flexible tail for Design I, finite element analysis for deflection analysis are performed for Design II.