A connection between state-space and doubly coprime fractional representations

Abstract-This paper deals with robust iterative learning control design for uncertain single-input-single-output linear time-invariant systems. The design procedure is based upon solving the robust performance condition using the Youla parameterization and the µ-synthesis approachto obtain a feedback controller. Thereafter, a convergent iterative learning law is obtained by using the performance weighting function involved in the robust performance condition. Experimental results, on a CRS465 robot manipulator, are provided to illustrate the effectiveness of the proposed design method.

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“…As shown in [8], [18], and [29], transfer functions N 1 (s), N 2 (s), X(s), and Y (s) can be obtained using the following procedure.…”

Section: Robust Ilc Design Via µ-Synthesismentioning

confidence: 99%

Robust Iterative Learning Control Design: Application to a Robot Manipulator

Tayebi

Abdul

Zaremba

et al. 2008

IEEE/ASME Trans. Mechatron.

102

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“…Q 2 2 RH 1 , the disturbance observer can be designed using H 1 theory in terms of Q 2 (s) (and hence Q). More speci…cally, to attenuate the in ‡uence of the disturbances, the design is performed by minimising the H 1 norm of the transfer function matrix from the disturbances to the outputs in terms of Q 2 and, according to Theorem 2 and Corollary 3, the stability of the closed-loop system under the DOBC with Q = V 1 Q 2 N is guaranteed for any Q 2 yielded by H 1 optimisation (Zhou and Doyle (1998) Then it is easy to constitute a doubly coprime factorisation of G and an LQG controller K 0 which stabilises the system (Nett et al (1984)). …”

Section: Q …Lter Designmentioning

confidence: 98%

Active Steering of Railway Vehicles via Dobc Techniques

Dong

Chen

Goodall

2005

IFAC Proceedings Volumes

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A novel control scheme for the active steering of railway vehicles is presented in the paper using disturbance observer based control (DOBC) techniques. In contrast to existing DOBC schemes which are mainly for singleinput-single-output (SISO) systems and designed by trial and error, a new DOBC technique for multi-input-multi-output (MIMO) systems is developed. This is achieved by reforming the DOBC into the parameterisation of all stabilising controllers and then the disturbance observer is designed to minimise the in ‡uence of disturbances. In this scheme, the disturbance observer does not have in ‡uence on tracking/regulation performance and stability. The developed DOBC scheme is then applied to the control of railway vehicles, where an LQG controller is designed as the primal controller for the vehicle running on straight tracks and the disturbance observer is employed to improve the curving performance. This overcomes the di¢ culty in compromising the performance and wheelset stability on straight tracks and the curving performance when a single controller is used. The simulation reveals that the curving performance of railway vehicles is improved while the straight track performance/wheelset stability remains the same.

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“…The transfer function of the plant is Figure Error! No text of specified style in document.. 8 Step response for the oscillating system…”

Section: Second Stepmentioning

confidence: 99%