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This paper focuses on the data-driven adaptive control problem of the shape memory alloy (SMA) actuators subject to uncertainties, input saturation and prescribed performance. Firstly, the uncertainties estimation method, anti-windup technology, and prescribed performance function are introduced to deal with uncertain nonlinearity, input constraint, and prespecified performance, respectively. Meanwhile, a general approach about designing asymmetrical convergence bound is presented to increase the flexibility of creating convergence area. Secondly, taking uncertainties, input saturation, and asymmetrical convergence bound into consideration, we design an integral terminal sliding mode controller to guarantee the prescribed tracking accuracy without using the knowledge of the SMA actuators model. Further, the stability of the controller and the boundedness of the convergence error are proved by rigorous theoretical analysis. Finally, the success and superiority of our controller are verified by the SMA actuator experiments. • A new data-driven control scheme is proposed for the uncertain shape memory alloy (SMA) actuators with input saturation. • The error convergence rate, maximum overshoot, and tracking accuracy can be guaranteed, while the input constraints and uncertainties exist. • A general method for designing asymmetrical convergence bound is presented. • The structure of the proposed controller is simple without using neural networks or fuzzy logic systems. [ABSTRACT FROM AUTHOR]

This article is concerned with the fault-tolerant tracking control problem for pneumatic continuum manipulator (PCM) systems with actuator faults. Conventional control strategies applied to PCMs have difficulty addressing the tracking control issue for systems subject to actuator faults. In this article, we provide a robust fault-tolerant control strategy for solving this issue. We first present an error transformation approach that possesses potential robustness against model uncertainties and unknown actuator faults. To relax certain restrictions in the error transformation approach, we then adopt a tuning function to adjust the error variables. By doing so, global stability of the closed-loop system is ensured. Finally, the effectiveness of this control strategy is validated through experiments on a PCM. [ABSTRACT FROM AUTHOR]

Atomic force microscope (AFM) has been defined as the one of the most powerful instruments to explore micro/nanoworld in various fields. To lower imaging noise, AFMs are commonly equipped with open-loop nanopositioners (scanners). However, the hysteretic effect of the AFM positioners is a dominate factor that increases the position error during AFM-based manipulations. To reduce hysteresis, inverse compensation approach is an effective solution. Normally, one compensator is designed for the manipulation task with maximum working range, which may not be efficient enough for maintaining uniform accuracy for tasks with different working ranges. The objective of this study is to develop a working-range adapted compensator to tackle this challenge. First, a generalized method that can precisely model various types of hysteresis is required. To fulfill this, a flexible Prandtl–Ishlinskii (PI) type model, named extended unparallel PI model, is employed. Based on this model, an implicit hysteresis compensation approach is developed, and its stability condition and control gain optimization approach are proposed. Combining the modeling and compensation approaches, a working-range adapted hysteresis compensator is finally established. Experimental results demonstrate that the mean control errors of the compensator are uniformly below $5\%$ in different working ranges. [ABSTRACT FROM PUBLISHER]

McKibben muscles have been shown to have improved stiffness characteristics when operating hydraulically. However when operating pneumatically, they are compliant and so have potential for safer physical human–robot interaction. This paper presents a method for rapidly switching between pneumatic and hydraulic modes of operation without the need to remove all hydraulic fluid from the actuator. A compliant and potentially safe pneumatic mode is demonstrated and compared with a much stiffer hydraulic mode. The paper also explores a combined pneumatic/hydraulic mode of operation which allows both the position of the joint and the speed at which it reacts to a disturbance force to be controlled. [ABSTRACT FROM AUTHOR]

Due to less appropriate sensors for representing the pose of soft robotic hand, the soft robotic hand usually works in an open loop control system. In this paper, only two simple sensors were used in a soft pneumatic gripper (SPG) control system to make it possess innervated-like ability. The control system was conducted with only two sensors, air pressure sensor and bending sensor where the air pressure sensor is able to detect grasping force and the bending sensor is able to detect grasping position The bending sensor was characterized by testing on pressure vs. bending and bending vs. size relationships. The principle of circular-shaped object size recognition was presented in Algorithm 1. Multi-group tests had been done on grasping different size and material objects, and test results had a strong effect on size recognition ability of the SPG. Finally, adaptive grasping control process was presented in Algorithm 2. The tests on grasping the same size objects had been done. The test results demonstrate that the SPG is able to maintain stable grasping state for a long time based on size recognition ability no matter what material the object is. At the same time, it had no effect on the grasping state at the time of existing disturbance, which had been verified by four different disturbance tests. The SPG will benefit the development of soft robotics field in picking and sorting fruits and vegetables, and an application of the SPG affixed on the home-made palletizing robot was described and conducted at last. [ABSTRACT FROM AUTHOR]