Work

Interval compression‐based model‐free control algorithm for reducing actuator execution frequency

Year: 2024

Type: article

Abstract: The complexity of real‐world systems poses challenges to model‐based control, sparking significant interest in model‐free control methods. By depending exclusively on the system's input–output data, the proposed method eliminates the need to construct intricate internal system models. The implementation is straightforward, can satisfy bounded control inputs, and allows for arbitrary adjustment of the actuator's execution frequency. The proposed method establishes an iterative mechanism under the constraint of bounded control inputs. It guarantees the algorithm's convergence by ensuring the continuous narrowing of the control interval. Furthermore, the update conditions within the iterative strategy can adapt to extremely low and continuously adjusting actuator execution frequencies. The bounded stability of the control method is proven using the continuity definition of functions. Its effectiveness and feasibility are validated through simulation and experimental verification.

Source: IET Control Theory and Applications

DOI: 10.1049/cth2.12775

Authors: Yitong Zhou, Jing Chang, Weisheng Chen, Hao Dai

Institution: Xidian University

Language: English

Topic: Iterative Learning Control Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,300

Funder: National Natural Science Foundation of China