Integrating instrumentation and control design

Lǚ, Jianbo; Skelton, Robert E.

doi:10.1080/002071799220722

Cited by 22 publications

(8 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Theorem 1: For a plant described in (1) with outputs defined in (10), there exists a dynamic output feedback controller such that the cost and performance constraints (9) are satisfied if and only if there exist matrices R, L, F, Q, X, Y, Z and diagonal matrix Γ such that…”

Section: The Problem Formulationmentioning

confidence: 99%

“…It is reasonable to assume that the price of a component is proportional to its precision [9], which is inversely proportional to the covariance of its noise. Hence the instrument cost can be expressed in term of the noise covariance matrix W a and W s .…”

Section: The Problem Formulationmentioning

confidence: 99%

“…The technique that we developed to determine the precision of each sensor/actuator is called economic design [9]. It is reasonable to assume that the price of a component is proportional to its precision [9], which is inversely proportional to the covariance of its noise.…”

Section: The Problem Formulationmentioning

confidence: 99%

See 2 more Smart Citations

Sensor/actuator selection for tensegrity structures

Skelton

2006

Proceedings of the 45th IEEE Conference on Decision and Control

Self Cite

View full text Add to dashboard Cite

In this paper the sensor/actuator selection for the control of tensegrity structures is investigated from a system design approach. Two methods with different levels of complexity are proposed to find the necessary precision for each sensor/actuator to satisfy specific input/output performance constraints. To determine the minimum number and the locations of the sensors and actuators, a heuristic algorithm iteratively deletes the sensor or actuator which requires the least precision until loss of feasibility. This algorithm results simultaneously the necessary number, the location and precision for each sensor/actuator. A tensegrity structure example has been solved as an application of the proposed algorithms.

show abstract

Section: The Problem Formulationmentioning

confidence: 99%

Section: The Problem Formulationmentioning

confidence: 99%

See 1 more Smart Citation

Sensor/actuator selection for tensegrity structures

Skelton

2006

Proceedings of the 45th IEEE Conference on Decision and Control

Self Cite

View full text Add to dashboard Cite

show abstract

“…Although this formulation resulted in a MILP problem (that can be easily solved to a global optimum), it also assumed that perfect control could be implemented. Lu and Skelton and Skelton and Li also employ an economic perspective. While these methods guarantee an implementable feedback element, the resulting nonlinear optimization was solved using local search methods.…”

Section: Introductionmentioning

confidence: 99%

“…Peng and Chmielewski and Ahmed et al proposed a formulation similar to Refs. and , but subsequently transformed the problem to a MICP. This MICP was solved using a branch and bound algorithm nearly identical to that used in Ref.…”

Section: Introductionmentioning

confidence: 99%

Covariance‐based hardware selection part IV: Solution using the generalized benders decomposition

2016

View full text Add to dashboard Cite

Recently the covariance based hardware selection problem has been shown to be of the mixed integer convex programming (MICP) class. While such a formulation provides a route to global optimality, use of the branch and bound search procedure has limited application to fairly small systems. The particular bottleneck is that during each iteration of the branch and bound search, a fairly slow semi-definite programming (SDP) problem must be solved to its global optimum. In this work, we illustrate that a simple reformulation of the MICP and subsequent application of the generalized Benders decomposition algorithm will result in massive reductions in computational effort. While the resulting algorithm must solve multiple mixed integer linear programs, this increase in computational effort is significantly outweighed by the reduction in the number of SDP problems that must be solved.

show abstract

Basic Concepts of Bioprocess Control

Dochain¹,

Harmand²

2008

Bioprocess Control

View full text Add to dashboard Cite

Integrating instrumentation and control design

Cited by 22 publications

References 5 publications

Sensor/actuator selection for tensegrity structures

Sensor/actuator selection for tensegrity structures

Covariance‐based hardware selection part IV: Solution using the generalized benders decomposition

Basic Concepts of Bioprocess Control

Contact Info

Product

Resources

About