A New Method for the Self-Tuning Control of Nonminimum Phase Discrete-Time Systems in the Presence of Disturbances

Lü, Jianming; Shafiq, Muhammad; Yahagi, Takashi

doi:10.1541/ieejeiss1987.117.2_110

Cited by 5 publications

(1 citation statement)

References 6 publications

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“…Such as in continuous time system, number of poles and zeros or the limit of upper bounds on the order of the plant are assumed to be known [1], [2], [3], [4]. Again the known time delay is crucial for discretetime systems [5], [6], [7]. To overcome these difficulties, the adaptive control methods were developed.…”

Section: Introductionmentioning

confidence: 99%

Time Varying Back Propagating Algorithm for MIMO Adaptive Inverse Controller

Mehedi¹

2017

ijacsa

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Abstract-In the field of automatic control system design, adaptive inverse is a powerful control technique. It identifies the system model and controls automatically without having prior knowledge about the dynamics of plant. In this paper neural network based adaptive inverse controller is proposed to control a MIMO system. Multi layer perception and back propagation are combinedly used in this investigation to design the NN learning algorithm. The developed structure represents the ability to identify and control the MIMO system. Mathematical derivation and simulation results for both plant identification and control are shown in this paper. Further, to prove the superiority of the proposed technique, performances are compared with recursive least square (RLS) method for the same MIMO system. RLS based adaptive inverse scheme is discussed in this paper for plant identification and control. Also the obtained simulated results are compared for both plant parameter estimation and tracking trajectory performance.

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