Linear Quadratic Control of Positive Systems: A Projection-Based Approach

Yang, Nachuan; Tang, Jiawei; Wong, Yik Ben; Li, Yuzhe; Shi, Ling

doi:10.1109/tac.2022.3172237

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Book1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A Quasilinear Quadratic Tracking Method for Systems With Saturating Actuators

He,

Li,

et al. 2024

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

Linear quadratic tracker (LQT) is usually employed to solve unconstrained tracking problems but falls short when dealing with systems exhibiting actuator saturation. This paper presents a novel quasilinear quadratic tracking method specifically designed to address this scenario. Firstly, the stochastic linearization (SL) approach is utilized to approximate the saturation nonlinearity with equivalent gains and biases using statistical properties of its input, which are thus incorporated into the system model so as to eliminate the nonlinearity. Then, different time scales are applied in the tracking controller and states in order to improve tracking accuracy. In addition, to reduce computational complexity, two algorithms are provided for approximating the equivalent gains and biases, catering to both scalar and vector control signals. Finally, the proposed algorithms are evaluated through numerical examples, demonstrating their effectiveness and superior tracking performances.

show abstract