Iterative Feedback Tuning of Cascade Control of Two-Inertia System

Jung, Hanul; Jeon, Kiho; Kang, Jae-Gu; Oh, Sehoon

doi:10.1109/lcsys.2020.3005803

Cited by 23 publications

(6 citation statements)

References 12 publications

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“…where k ∈ z + . Combining Equations ( 26), (25), and ( 12), ΔT (k) is subject to the following constraints:…”

Section: Pseudo Partial Derivative Estimationmentioning

confidence: 99%

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Data‐driven consistent control with data compensation for a class of unknown nonlinear multiagent systems with constraints

Liu

et al. 2023

IET Control Theory & Appl

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To solve the problem of longitudinal cooperative formation driving control of multiple vehicles, a novel model‐free adaptive control algorithm with data compensation under constraint conditions (COM‐cMFAC) is proposed in this manuscript. In the COM‐cMFAC algorithm, the pseudo partial derivative (PPD), which is a time‐varying parameter, is used to linearize the nonlinear dynamics of the multivehicle cooperative system by using dynamic linearization technology. Then, a COM‐cMFAC controller is designed. For the case of data packet loss, the proposed controller uses a data compensation mechanism that estimates and compensates for the lost data through the data collected at the previous moment to perform packet loss control. Additionally, the controller considers the constrained input and output problems that will occur in the actual control process and imposes input and output constraints. The main advantage of the COM‐cMFAC algorithm is that the entire control process only needs the input and output data of the multivehicle cooperative system, and it also has a good control effect in the case of packet loss. The stability of the proposed method is verified through strict mathematical analysis, and its effectiveness is verified by semiphysical experiments based on a MATLAB/Simulink and Carsim platform connection environment.

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“…where k ∈ z + . Combining Equations ( 26), (25), and ( 12), ΔT (k) is subject to the following constraints:…”

Section: Pseudo Partial Derivative Estimationmentioning

confidence: 99%

“…It has an ideal control effect and strong robustness for nonlinear systems. To date, the MFAC algorithm has found extensive applications in many fields, including autonomous car control [23], robot manipulator control [24], injection modelling processes [25], and the chemical industry [26].…”

Section: Introductionmentioning

confidence: 99%

Data‐driven consistent control with data compensation for a class of unknown nonlinear multiagent systems with constraints

Liu

et al. 2023

IET Control Theory & Appl

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“…To achieve higher robust stability, Kawai et al [7] proposed a high-robustness force control method based on the duality of two-inertia systems, validated by numerical simulations and experiments for their robustness against environmental stiffness changes. Jung et al [8] proposed a new iterative feedback tuning method for cascade control in two-inertia systems. This method included position and speed errors in the cost function, and has been proven effective under various conditions through experiments.…”

Section: Introductionmentioning

confidence: 99%

On V-Geometric Ergodicity Markov Chains of the Two-Inertia Systems

Hu,

2024

Mathematics

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This study employs the diffusion process to construct Markov chains for analyzing the common two-inertia systems used in industry. Two-inertia systems are prevalent in commonly used equipment, where the load is influenced by the coupling of external force and the drive shaft, leading to variations in the associated output states. Traditionally, the control of such systems is often guided by empirical rules. This paper examines the equilibrium distribution and convergence rate of the two-inertia system and develops a predictive model for its long-term operation. We explore the qualitative behavior of the load end at discrete time intervals. Our findings are applicable not only in control engineering, but also provide insights for small-scale models incorporating dual-system variables.

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“…The auto-tuning of controllers can be categorized into two groups: one is the model-based manual approach and the other is the model-free automatic approach [23] [24]. Hanul et al propose a novel iterative feedback tuning method for cascaded control, but it lacks a systematic evaluation of the wireless network performance, and the simultaneous correlation between communication and control performances is not elaborated [25]. A modified cascade control strategy on the basis of the internal model control (IMC) principle is proposed by Fan et al for dominating a class of unstable processes with large delay times [26].…”

Section: Introductionmentioning

confidence: 99%

Latency-Aware Control for Wireless Cloud Fog Automation: Framework and Case Study

Lyu¹,

Bengtsson²,

Nilsson³

et al. 2023

Preprint

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<p>The development of wireless communication has indeed promoted cloud fog automation in the industry. It also introduces new issues of reliability and latency for control systems. This study sought to investigate the impacts of the commonly used industrial wireless network on the control performance parameters using a ball-and-beam (BB) time-critical balancing control system. An internal model control-inspired latency-aware wireless control framework (IMC-LA) is presented and employed in the BB system to handle the time delays and instability-creating elements introduced by wireless communication. A preliminary control assessment of the BB system under two new-generation wireless technologies, Wi-Fi 6 and 5G, was delivered. The correlation between network performance and control performance was analyzed statistically compared to the wired Ethernet condition. Test results show a dramatic decrease in position error after utilizing the proposed latency-aware wireless control framework. This study provides practical insights into the potential impacts of industrial wireless networks on control systems with a workable latency-aware wireless control approach.</p>

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Iterative Feedback Tuning of Cascade Control of Two-Inertia System

Cited by 23 publications

References 12 publications

Data‐driven consistent control with data compensation for a class of unknown nonlinear multiagent systems with constraints

Data‐driven consistent control with data compensation for a class of unknown nonlinear multiagent systems with constraints

On V-Geometric Ergodicity Markov Chains of the Two-Inertia Systems

Latency-Aware Control for Wireless Cloud Fog Automation: Framework and Case Study

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