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This paper aims to design an event-triggered adaptive prescribed performance controller for flexible manipulators, with the primary objectives of achieving output performance constraints and addressing communication resource limitations.

The authors propose a novel prescribed performance barrier Lyapunov function (PP-BLF) that considers both output and tracking performance constraints. The PP-BLF ensures that the system's output, transient behavior and steady-state performance, adhere to prescribed constraints. The boundary of the PP-BLF is established by an exponential function that decays over time. Notably, the PP-BLF can be applied seamlessly in unconstrained cases without necessitating controller redesign. Moreover, the controller design incorporates an event-triggered mechanism, effectively reducing the frequency of controller updates and optimizing the utilization of communication resources. Additionally, the authors employ adaptive techniques to estimate the system's unknown parameters and approximate unknown nonlinear functions using radial basis function neural networks (RBFNN). To address the challenge of “complexity explosion”, dynamic surface technology is employed.

Numerical simulations are conducted under five different cases to verify the effectiveness of the proposed controller. The results demonstrate that the controller successfully constrains the output tracking error within the prescribed performance boundary. Moreover, compared with the traditional time-triggered mechanism, the event-triggered mechanism significantly reduces the controller's update frequency, resolving the problem of limited communication resources.

The paper reduces the update frequency of control signals and improves resource utilization through an event-triggered mechanism in the form of relative thresholds. The authors recognize that the event-triggered mechanism may impact the output performance of the system. To address this challenge, the authors propose a prescribed performance Barrier Lyapunov Function (PP-BLF). The PP-BLF is designed to effectively constrain the output performance of the system, ensuring satisfactory control even when the control signal updates are reduced.

City wall is an important symbol of ancient Chinese cities with unique geographical and cultural characteristics. Thus, the preservation of this historic landmark is considered significantly important. However, numerous residential construction activities and changes in ecological environment have destructed a great portion of the city walls in recent years. This study looks into the preservation of the ancient city walls from the systematic perspective and in line with the actual characteristics of Longdong Region to provide guideline measures for the protection and restoration of such landmark. Cognition and preservation are adopted extensively to investigate the specific situation of and the factors that influence the ancient city walls in this region. Preservation strategies for the city walls, including the “Axis-Point” system, planning control, and authenticity readability, are presented. The ancient city walls in Longdong Region can be preserved by protecting the entire region, the city, and the main wall body. The systematic method and preservation strategies at the “macro perspective,” “medium perspective” and “micro perspective” levels can solve the preservation problems of the ancient city walls in Longdong Region effectively.