Traditional approaches for monitoring human gait have severe spatial and temporal restrictions with complex analysis methods and high cost, which are powerless to promote the development of intelligent life involving fitness, sport training, and healthcare. Herein, a portable smart insole system with high spatial resolution and simple manufacturing process to measure plantar pressure distribution anytime, anywhere for gait analysis is proposed. An insole‐shaped array of 104 piezoresistive sensors with highly robust characteristics is assembled, exhibiting a good pressure‐sensing uniformity. The smart insole not only detects the subtle displacement of the center of gravity of the body, but also exhibits a real‐time, high‐resolution thermodynamic diagram of the plantar pressure distribution during human activities. More importantly, the function of motion intelligence identification can be realized by regionalizing and digitizing the whole plantar pressure distribution, achieving an average recognition accuracy of 83.32% among six predefined motions. These results imply that the carbon fiber‐based smart insole can provide an effective approach for convenient gait analysis and motion identification, which has a great potential in the application of future intelligent life.
This paper introduces a method to navigate the tower crane movement and suppress the payload swing synchronously. Special error signals are introduced, which bring the coupling of dynamics among various states of the crane and enable the control to meet the synchronous operation in practice. The special angle-dependent energy functions are designed as the candidate sub-Lyapunov functions for decoupling the states. The controller is then stepwise designed with the help of the dynamics model. The stability of the control is proven in the Lyapunov sense. Extensive simulations and experiments have been carried out to demonstrate the effectiveness of the proposed nonlinear coupling control. A popular control approach in the literature is chosen to compare with the current work. It is found that the proposed control is quite effective in suppressing the payload swing while tracking the pre-determined path at the same time.
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