Design of a Data-Driven PID Controller

Yamamoto, Toru; Takao, Kenji; Yamada, Takumi

doi:10.1109/tcst.2008.921808

Cited by 167 publications

(93 citation statements)

References 11 publications

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“…Yamamoto proposed data-based proportionalintegral-differential (PID) control that tuned PID parameters with data and broadened the traditional PID method [45]. Hjalmarsson proposed iterative feedback tuning that found the optimal controller parameters using the data of closed-loop system and gradient-based iteration.…”

Section: Outline For Direct Controller Design Methods Based On Datamentioning

confidence: 99%

Data-based intelligent modeling and control for nonlinear systems

Sun

2011

Front. Electr. Electron. Eng. China

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With the ever increasing complexity of industrial systems, model-based control has encountered difficulties and is facing problems, while the interest in data-based control has been booming. This paper gives an overview of data-based control, which divides it into two subfields, intelligent modeling and direct controller design. In the two subfields, some important methods concerning data-based control are intensively investigated. Within the framework of data-based modeling, main modeling technologies and control strategies are discussed, and then fundamental concepts and various algorithms are presented for the design of a data-based controller. Finally, some remaining challenges are suggested.

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Section: Outline For Direct Controller Design Methods Based On Datamentioning

confidence: 99%

Data-based intelligent modeling and control for nonlinear systems

Sun

2011

Front. Electr. Electron. Eng. China

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“…The model-free control is based on an continuously updated local modeling via the unique knowledge of the input-output behavior [4]. Whereas the former requires to look for a model using the usual black box identification, which is valid within an operating range.…”

Section: Data Basedmentioning

confidence: 99%

“…In model-free methods [3,4], the explicit identification of significant model points or a parametric model is not used. Whereas a local modeling is continuously updated via the knowledge of the input-output behavior.…”

Section: Introductionmentioning

confidence: 99%

Data Based Lower-Order Controller Design: Moment Matching Approach

Kim¹,

Jin²

2012

The Transactions of The Korean Institute of Electrical Engineer

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-This paper presents a data based low-order controller design algorithm for a linear time-invariant process with a time delay. The algorithm is composed by combining an identification step based on open loop pulse test with a low-order controller design step to obtain the entire set of controllers achieving multiple performance specifications. The initial information necessary for this algorithm are merely the width and amplitude of a rectangular pulse, a controller of four types (PI, PD, PID, first-order), and design objectives. Various parametric approaches that have been developed are merged in the controller design algorithm. The resulting controller set satisfying the design objectives are displayed on the 2D and 3D graphics and thus it is very easy for us to pick a controller inside the admissible set because we can check the corresponding closed-loop performances visually.

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“…In this study, the design of a data-oriented cascade control system based on Kansei is proposed. In the proposed control system, there are two controllers which are a data-driven controller 1 and a fixed controller. In particular, a data-driven controller 1 determines the suitable reference signal of a welfare equipment based on Kansei.…”

Section: Introductionmentioning

confidence: 99%

Design of a Data-Oriented Kansei Feedback Control System

Kinoshita¹,

Yamamoto²

2017

JRNAL

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In the development of the aging society, it is important for patients with hemiplegia to introduce adaptive welfare equipment. However, it is difficult to determine the suitable reference signal for each person. In this study, the design of a data-oriented cascade control system based on Kansei is proposed. In the proposed control system, there are two controllers which are a data-driven controller and a fixed controller. In particular, a data-driven controller determines the suitable reference signal based on Kansei.

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Design of a Data-Driven PID Controller

Cited by 167 publications

References 11 publications

Data-based intelligent modeling and control for nonlinear systems

Data-based intelligent modeling and control for nonlinear systems

Data Based Lower-Order Controller Design: Moment Matching Approach

Design of a Data-Oriented Kansei Feedback Control System

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