Adaptive Practical Predefined-Time Control for Uncertain Teleoperation Systems With Input Saturation and Output Error Constraints

Li, Longnan; Liu, Zhengxiong; Guo, Shaofan; Ma, Zhiqiang; Huang, Panfeng

doi:10.1109/tie.2023.3250752

Cited by 19 publications

(5 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The direct method is the most widely used. It has been applied to various applications such as self-piloted crafts [20][21][22], robotics [23][24][25], power systems [26,27], including induction motors [28][29][30]. However, the combined method proposed in the work [31] aims to improve the transient performance beyond the direct and indirect dynamic methods.…”

Section: Of 20mentioning

confidence: 99%

Robust Combined Adaptive Passivity-Based Control for Induction Motors

Travieso-Torres,

Ricaldi-Morales,

Aguila-Camacho

2024

Preprint

View full text Add to dashboard Cite

The need for industrial and commercial machinery to maintain high torque while accurately following a variable angular speed is increasing. To meet this demand, induction motors (IMs) are commonly used with variable speed drives (VSDs) that employ a field-oriented control (FOC) scheme. Over the last thirty years, IMs have been replacing independent connection direct current motors due to their cost-effectiveness, reduced maintenance needs, and increased efficiency. However, IMs and VSDs exhibit nonlinear behavior, uncertainties, and disturbances. This paper proposes a robust combined adaptive passivity-based control (CAPBC) for this class of nonlinear systems that applies to angular rotor speed and stator current regulation inside an FOC scheme for IMs´ VSDs. It uses general Lyapunov-based design energy functions and adaptive laws with σ-modification to assure robustness after combining control and monitoring variables. Lyapunov’s second method and Barbalat Lemma prove that the control and identification error tends to be zero over time. Moreover, comparative experimental results with standard Proportional Integer controller (PIC) and direct APBC, show the proposed CAPBC effectiveness and robustness under normal and changing conditions

show abstract

Section: Of 20mentioning

confidence: 99%

Robust Combined Adaptive Passivity-Based Control for Induction Motors

Travieso-Torres,

Ricaldi-Morales,

Aguila-Camacho

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Based on the fixed/predefined convergence theory [44][45][46], the practical fixed/predefined formation controllers can be extended by using the Theorem 2.…”

Section: Alg-based Cooperative Strategymentioning

confidence: 99%

“…According to (46) and ( 49), the controlled errors can be steered to a predefined compact set, and the formation zero-errors can be regulated. This completes the proof.…”

Section: Partial Time-varying Control Coefficientsmentioning

confidence: 99%

Adaptive Learning Gain based Resilient Control of Multiagent Systems with Partial Uncertain Control Coefficients Under FDI Attacks

Yang,

Long,

Lei

2023

Preprint

View full text Add to dashboard Cite

This paper presents a novel approach to security resilient control in collective multiagent systems, incorporating an adaptive learning gain mechanism. The proposed method addresses challenges posed by bounded external disturbances, partial false-data-injection (FDI) attacks on the actuators, and partial unknown time-varying control coefficients. The presented synthesized control consists of following parts. Specifically, a robust adaptive control law with implicit learning is proposed to address the modeling parameterized uncertainties and disturbances. An adaptive learning gain-based control technique is designed to reduce the adversarial effect caused by mismatched disturbances with time-varying parameters, which curbs the cooperative errors to the assigned field. A resilient control approach is established to mitigate the detrimental impact of malicious attacks on actuators. An adaptive control strategy, utilizing a novel congelation of variables, is implemented to address the control issue pertaining to partially unknown control coefficients. This technique ensures that control inputs align with the practical actuators by establishing feasible control bounds. The property of the resulting closed-loop error multiagent systems is analyzed. Finally, the efficacy of the designed controller is illustrated by providing an illustrative example.

show abstract

“…When modeling a GRN, it is known that there exist many uncertain factors, such as environmental changes, external interference, and experimental noises, which may hinder the effectiveness of control schemes (Liu et al, 2023;Yu et al, 2022). To align with the dynamical behaviors of the practical systems, it is essential to model Boolean control networks with disturbances (DBCNs).…”

Section: Introductionmentioning

confidence: 99%

Design of all feasible output feedback controllers for robust output tracking of Boolean control networks

Deng,

Fu,

Cao

et al. 2024

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

This paper devotes to the design of all feasible output feedback controllers for the robust output tracking of Boolean control networks with disturbances (DBCNs). First, the output feedback–based robust control invariant set (RCIS) is defined, and a calculation method to find all output feedback–based RCISs of a given set is derived via the truth matrix technique. Second, a class of complete family of robust reachable sets (CFRRSs) is developed; the solvability of robust output tracking problem by output feedback control is verified. Furthermore, a constructive algorithm of all feasible output feedback controllers is presented. Finally, the study of a network about Escherichia coli lactose operon shows the effectiveness of the theoretical results.

show abstract

Adaptive Practical Predefined-Time Control for Uncertain Teleoperation Systems With Input Saturation and Output Error Constraints

Cited by 19 publications

References 25 publications

Robust Combined Adaptive Passivity-Based Control for Induction Motors

Robust Combined Adaptive Passivity-Based Control for Induction Motors

Adaptive Learning Gain based Resilient Control of Multiagent Systems with Partial Uncertain Control Coefficients Under FDI Attacks

Design of all feasible output feedback controllers for robust output tracking of Boolean control networks

Contact Info

Product

Resources

About