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Origami offers a promising alternative for designing innovative soft robotic actuators. While features of origami, such as bi-directional motion and structural anisotropy, haven't been extensively explored in the past, this letter presents a novel design inspired by origami tubes for a bi-directional actuator. This actuator is capable of moving in two orthogonal directions and has separate channels throughout its body to control each movement. We introduce a bottom-up design methodology that can also be adapted for other complex movements. The actuator was manufactured using popular 3D printing techniques. To enhance its durability, we experimented with different 3D printing technologies and materials. The actuator's strength was further improved using silicon spin coating, and we compared the performance of coated, uncoated, and silicononly specimens. The material model was empirically derived by testing specimens on a universal testing machine (UTM). Lastly, we suggest potential applications for these actuators, such as in quadruped robots.

This paper considers the problem of adaptive fault estimation and fault‐tolerant tracking control for a class of uncertain nonlinear systems with model uncertainty and process fault. By utilising the approximation abilities of fuzzy logic systems, a novel fault estimation fuzzy observer is designed to estimate the unmeasured states, nonlinear functions and process fault. Based on backstepping technologies, a adaptive fuzzy fault‐tolerant controller with the adaptive updated laws is established, which can not only ensure the prescribed tracking performances, but also effectively compensate the process fault. It is proved that all the closed‐loop signals of systems are uniformly ultimately bounded and the tracking errors can constrain to the prescribed bounds. Finally, simulation results can verify the efficiency of the proposed approach.

Summary In this article, an adaptive output feedback neural tracking control algorithm is studied for non‐affine switched systems with multiple time delays and actuator faults. First, an adaptive neural state observer, which only needs to update a parameter online, is presented to estimate the unmeasurable state, and Lipschitz condition is used to deal with delay fault so as to avoid complex delay assumption. Then, by using online estimation information and backstepping technique, a switched fault‐tolerant control mechanism is established for non‐affine switched systems, the designed controller of each subsystems can ensure that non‐affine switched systems output signal can track reference signal under switch signals with average dwell time and all closed‐loop signals are bounded in the presence of multiple time delays, actuator faults, and external disturbances. Finally, simulation results verify the effectiveness of the proposed algorithm.

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