Current Issue : January-March Volume : 2024 Issue Number : 1 Articles : 5 Articles
Soft robots are interesting examples of hyper-redundancy in robotics. However, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials make modeling these robots more complicated. This study presents a geometric inverse kinematics (IK) model for trajectory tracking of multi-segment extensible soft robots, where each segment of the soft actuator is geometrically approximated with a rigid links model to reduce the complexity. In this model, the links are connected with rotary and prismatic joints, which enable both the extension and rotation of the robot. Using optimization methods, the desired configuration variables of the soft actuator for the desired end-effector positions were obtained. Furthermore, the redundancy of the robot is applied for second task applications, such as tip angle control. The model’s performance was investigated through kinematics and dynamics simulations and numerical benchmarks on multisegment soft robots. The results showed lower computational costs and higher accuracy compared to most existing models. The method is easy to apply to multi-segment soft robots in both 2D and 3D, and it was experimentally validated on 3D-printed soft robotic manipulators. The results demonstrated the high accuracy in path following using this technique....
In this paper, an actuator fault diagnosis scheme based on the backstepping method is proposed for a class of nonlinear heat equations. The fault diagnosis scheme includes fault detection, fault estimation and time to failure (TTF) prediction. Firstly, we achieve fault detection by comparing the detection residual with a predetermined threshold, where the detection residual is defined as the difference between the observer output and the system measurement output. Then, we estimate the fault function through the fault parameter update law and calculate the TTF using only limited measurements. Finally, the numerical simulation is performed on a nonlinear heat equation to verify the effectiveness of the proposed fault diagnosis scheme....
Monitoring the condition of the aircraft actuators in various operating and environmental circumstances, this paper presents a method for measuring the surface roughness of aircraft actuators. The proposed method starts with the current and vibration signal as failure indicators and a dual-tree complex wavelet transformation (DTCWT) to generate the necessary features. Timedelay neural networks (TDNNs) have been developed for real-time performance monitoring to categorize problems and determine their severity. The simulation results show that the suggested method can accurately identify various faults....
To overcome the problems of the low power/weight ratio of traditional servo motors, complex transmission systems, and large space occupied by hydraulic drive systems, this paper designs a bidirectional torsional actuator using the shape memory effect of Ti-Ni shape memory alloy (SMA) wire, which aims to realize the folding and unfolding of the wings of flying cars. The model of the designed actuator was established and the theoretical calculation was analyzed, based on which the experimental verification was carried out. It is found that when the heating current is 1.6 A, the mechanism can take into account the economy under the premise of meeting a certain folding speed. When the pre-stretching amount of SMA wire is 3%, the residual strain corresponding to the wire is small, about 0.577%, and it can provide driving torque and torsion angle to meet the design requirements of the actuator. This verifies the feasibility of the actuator and obtains the driving characteristics of the actuator. Finally, the shortcomings and improvement measures of the actuator are analyzed briefly....
A fixed-time event-triggered consensus control method is proposed for uncertain nonlinear multiagent systems with actuator failures. Since actuator failures, external disturbances and control gains are time-varying and completely unknown, the effects of these system constraints on the system are completely unknown, which makes the implementation of fixed-time tracking control challenging. To deal with these system constraints, radial basis function neural networks (RBFNNs) are applied to approximate the uncertain dynamics, and a boundary estimation method is presented to achieve adaptive compensation for them. Furthermore, considering that the implementation of this boundary estimation method requires a large number of communication resources, an event triggering mechanism is designed to reduce the update frequency of the controller. It is theoretically confirmed that using the proposed control scheme, all the followers can track the leader with sufficient accuracy in a predetermined time, and all the closed-loop signals are bounded. Finally, the simulation experiments verify the theoretical results....
Loading....