Parameterised controller synthesis for SISO-LTI uncertain plants using frequency domain information

Parastvand, Hossein; Khosrowjerdi, Mohammad Javad

doi:10.1080/00207721.2015.1022026

Cited by 7 publications

(5 citation statements)

References 20 publications

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“…The procedure for calculation the family of stabilizing PID controllers is summarized in the following algorithm [11]. In the proposed approach of Algorithm 1, roots of function in (8), can be obtained from (4) and the range of is calculated based on the value of . Also the range of admissible values obtain from (7) which have the slope equal to .…”

Section: Pid Controller Design: Model Free Approchmentioning

confidence: 99%

“…Another modelbased application with PID has been proposed in [4] on load motion control of two-mass servomechanisms. Although most of the proposed methods in this area rely on plant mathematical model, yet some model-free approaches can be found in the literature such as [5,6,7,8,18,19]. Almost every proposed model-free approach uses time domain data and online adaptive algorithms.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Position Control of Motor Drive Systems: A Data Driven Approach

Parastvand

Khosrowjerdi²,

M'Sirdi³

2015

Ren. Ener. & Sust. Dev.

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Section: Pid Controller Design: Model Free Approchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Position Control of Motor Drive Systems: A Data Driven Approach

Parastvand

Khosrowjerdi²,

M'Sirdi³

2015

Ren. Ener. & Sust. Dev.

Self Cite

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“…To address the sizing problem of existing and new CSs, we first partition the graph of EV network featuring only one CS (from the set of CSs located from the solution of CS placement) in each subgraph. Then, we use the Kharitanov theorem and zero exclusion condition [15] to transform the CS sizing problem to zero exclusion of the Kharitonov rectangles or polygonal polynomials of the closed loop system attained from the sub-graphs (or the problem of robust stability of plants with uncertain parameters [16]). Detailed simulations and analyses of the Tesla CS network of Sydney verify that the proposed approach has significant impact on reducing the waiting times at CSs in Year 2025 assuming 500% increase in EV traffic [19].…”

Section: Introductionmentioning

confidence: 99%

Robust Placement and Sizing of Charging Stations From a Novel Graph Theoretic Perspective

et al. 2020

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This paper proposes analytical approaches to extend the capacity of existing networks of electric vehicles (EVs) by placement of additional charging stations (CSs) as well as determining the sizes of existing and new CSs in order to handle future expansions of EVs. The EV flow at CSs is modeled by a graph where nodes are potential locations for CSs and edges are uncertain parameters representing the variable EV flow at CSs. The required extra CS locations are explored by transforming the CS placement problem into a controllability framework addressed by maximum matching principle (MMP). To find the sizes of each CS, the graph of CS network is partitioned featuring only one CS in each subgraph. The size of CS in each subgraph is then determined by transforming the problem into the problem of robust stability of a system with uncertain parameters where each parameter is associated with an edge of subgraph. The zero exclusion principle is then tested for the related Kharitonov rectangles and polygonal polynomials of closed loop system with selected feedback gain as CS capacity. The proposed analytical approach is tested on the existing Tesla CS Network of Sydney. The locations of extra required CSs as well as the sizes of existing and new CSs are determined to maintain the waiting times at all stations below the threshold level.

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“…The set of all stabilizing PID controllers with H ∞ performance is obtained using only the frequency-domain data in Keel and Bhattacharyya (2008). This method is extended to design of fixed-order linearly parameterized controllers in Parast-1 Corresponding author: alireza.karimi@epfl.ch vand and Khosrowjerdi (2015Khosrowjerdi ( , 2016. The frequency response data are used in Hoogendijk et al (2010) to compute the frequency response of a controller that achieves a desired closed-loop pole location.…”

Section: Introductionmentioning

confidence: 99%

A data-driven approach to robust control of multivariable systems by convex optimization

Karimi

Kammer

2017

Automatica

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The frequency-domain data of a multivariable system in different operating points is used to design a robust controller with respect to the measurement noise and multimodel uncertainty. The controller is fully parametrized in terms of matrix polynomial functions and can be formulated as a centralized, decentralized or distributed controller. All standard performance specifications like H2, H∞ and loop shaping are considered in a unified framework for continuous-and discrete-time systems. The control problem is formulated as a convex-concave optimization problem and then convexified by linearization of the concave part around an initial controller. The performance criterion converges monotonically to a local optimal solution in an iterative algorithm. The effectiveness of the method is compared with fixed-structure controller design methods based on non-smooth optimization via multiple simulation examples.

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Parameterised controller synthesis for SISO-LTI uncertain plants using frequency domain information

Cited by 7 publications

References 20 publications

Position Control of Motor Drive Systems: A Data Driven Approach

Position Control of Motor Drive Systems: A Data Driven Approach

Robust Placement and Sizing of Charging Stations From a Novel Graph Theoretic Perspective

A data-driven approach to robust control of multivariable systems by convex optimization

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