No abstract is provided for this article.
In this paper, a proxy-based sliding-mode control (PBSMC) approach is proposed for robust tracking control of a piezoelectric-actuated nanopositioning stage composed of piezoelectric stack actuators and compliant flexure mechanisms. The essential feature of the PBSMC approach is the introduction of a virtual coupling proxy, which is controlled by the sliding-mode controller (SMC) to track the desired position. Simultaneously, due to the virtual coupling, a proportional-integral-derivative (PID) controller on the other side of the proxy ensures the position of the end-effector of the stage to follow the position of the proxy. Therefore, the PBSMC guarantees the end-effector to track the desired trajectory. The advantages of the developed PBSMC lie in the facts that 1) the discontinuous signum function in the traditional SMC is omitted without any approximation. Hence, the output of the PBSMC is continuous, which does not suffer from the chattering phenomenon; and 2) the PBSMC laws are developed without having the necessity to include the nominal system model, hysteresis model or the state observer. Hence, the PBSMC provides a novel effective yet simple control method, which permits to avoid the lack of performances from PID and the chattering from SMC, and permits to combine the advantages from them. The stability of the closed-loop control system is proved through Lyapunov analysis. Finally, comparative studies are performed on a custom-built piezo-actuated stage. Experimental results show that the tracking errors of the PBCM are reduced by 74.22%, as compared to the traditional PID controller, with the desired sinusoidal trajectory under the 50-Hz input frequency, which clearly demonstrates the superior tracking performance of the PBSMC.
Hyper-redundant manipulators with slender body and high dexterity are widely applied for operations in confined spaces. Among the motion planning methods for these operations, the follow-the-leader motion controller is generally developed to avoid the obstacles, while the path trajectories are usually given. In this paper, we present an autonomous motion planner with a specialized rapidly exploring random tree (Sp-RRT) approach for follow-the-leader motion of hyper-redundant manipulators. Starting from the target pose in the workspace, the exploring tree can expand to multiple entrances while guaranteeing the final pose of the manipulator's end-effector. Meanwhile, the dexterity of hyper-redundant manipulators (even with different segments) can be utilized sufficiently with customized expanding parameters. Simulation results compared with existing methods are conducted to demonstrate the aforementioned characteristics and effectiveness. For further validation, we experimentally verify the development with our custom-built hyper-redundant manipulator to realize the generated path with follow-the-leader motion.
Artificial muscles, providing safe and close interaction between humans and machines, are essential in soft robotics. However, their insufficient deformation, output force, or configurability usually limits their applications. Herein, this work presents a class of lightweight fabric‐lattice artificial muscles (FAMs) that are pneumatically actuated with large contraction ratios (up to 87.5%) and considerable output forces (up to a load of 20 kg, force‐to‐weight ratio of over 250). The developed FAMs consist of a group of active air chambers that are zigzag connected into a lattice through passive connecting layers. The geometry of these fabric components is programmable to convert the in‐plane lattice of FAMs into out‐of‐plane configurations (e.g., arched and cylindrical) capable of linear/radial contraction. This work further demonstrates that FAMs can be configured for various soft robotic applications, including the powerful robotic elbow with large motion range and high load capability, the well‐fitting assistive shoulder exosuit that can reduce muscle activity during abduction, and the adaptive soft gripper that can grasp irregular objects. These results show the unique features and broad potential of FAMs for high‐performance soft robots.
This paper presents preliminary results on modeling and control of a quadrotor UAV. With aerodynamic concepts, a mathematical model is firstly proposed to describe the dynamics of the quadrotor UAV. Parameters of this model are identified by experiments with Matlab Identify Toolbox. A group of PID controllers are then designed based on the developed model. To verify the developed model and controllers, simulations and experiments for altitude control, position control and trajectory tracking are carried out. The results show that the quadrotor UAV well follows the referenced commands, which clearly demonstrates the effectiveness of the proposed approach. Keywords—Quadrotor UAV, Modeling, Control, Aerodynamics, System Identification.
The compliant structure and influence of external forces usually result in complex deformation of soft continuum robots, which makes the accurate modeling and control of the robot challenging. In this article, we present a new variable curvature kinematic modeling approach for soft continuum robots by taking the external forces into consideration, achieving both accurate motion simulation and feedforward control of the robot. To this end, the variable curvature configuration is first parameterized based on the absolute nodal coordinate formulation. Then, a kinematic model is developed to describe the mappings between the defined configuration space and the actuation space with payloads. With this model, we achieve accurate and fast motion simulation for the soft continuum robot with different payloads and input pressures within 1 ms, which is verified by a set of experiments. Finally, an inverse-model-based feedforward controller is developed for a two-section soft continuum robot. The experimental results of tracking complex trajectories verify the effectiveness of our model and control strategies. The average position error of the end effector is 2.89% of the robot length. This article can also be served as a tool to design and analyze soft continuum robots with a desired workspace.
This paper presents a trajectory tracking control strategy based on the subspace stabilization approach to accurately manipulate an under-actuated flying robot from a known initial state to the desired terminal state. To facilitate the development of this tracking strategy, the dynamical model of the quadrotor is firstly proposed. Subsequently, an optimal trajectory generation algorithm is adopted to generate dynamically consistent trajectories regarding the initial and terminal state constraints in specific missions. Then, a trajectory tracking control strategy based on the subspace stabilization approach is developed considering the lumped disturbances and time delays. The developed control strategy is applied for ball juggling of a highly under-actuated quadrotor, which is a popular flying robot in recent years. Real-time experimental results show that the quadrotor can be accurately manipulated from a known initial state to the desired terminal state within a given time horizon. In the consecutive juggling tasks, the quadrotor with a racket of radius 0.065 m can consecutively juggle the ball for averagely 4 hits in each rally, and a longest rally achieved by the developed control strategy is 14 hits. The feasibility of the developed control strategy is also preliminarily verified through the cooperative juggling between two quadrotors. All of these results demonstrate the effectiveness of the developed control strategy.
