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1

ANFIS and neural network techniques for non-parametric modelling of a twin rotor system

Toha S. F., Tokhi M. O.

Systems Science

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2010

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Vol. 36, no 4

13-31

EN

Interest in system identification especially for nonlinear systems has significantly increased in the past few decades. Soft-computing methods which concern computation in an imprecise environment have gained significant attention amid widening studies of explicit mathematical modelling. In this research, three different soft computing techniques that are multi-layered perceptron neural network using Levenberg-Marquardt (LM), Elman recurrent neural network and adaptive neuro-fuzzy inference system (ANFIS) network are deployed and used for modelling a twin rotor multi-input multi-output system (TRMS). The system is perceived as a challenging engineering problem due to its high nonlinearity, cross coupling between horizontal and vertical axes and inaccessibility of some of its states and outputs for measurements. Accurate modelling of the system is thus required so as to achieve satisfactory control objectives. It is demonstrated experimentally that soft computing methods can be effectively used for modelling the system with highly accurate results. The accuracy of the modelling results is demonstrated through validation tests including training and test validation and correlation tests.

2

Air motor system modelling using extended neural network algorithms

Marumo R., Tokhi M. O.

Systems Science

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2005

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Vol. 31, no 3

87-101

EN

This paper investigates the development of neuro-modelling approaches for a highly non-linear system. The work is motivated by the fact that the response of a pneumatic drive is very slow, which leads to inability of the system to attain set points due to high hysteresis. Also the dynamic model of the pneumatic system is highly non-linear, which greatly complicates controller design and development. To address these problem areas, two streams of research efforts have evolved. These are: using conventional methods to develop a modelling and control strategy and adopting a strategy that does not require mathematical model of the system. This paper presents an investigation into the modelling of an air motor incorporating a pneumatic equivalent of the electric H-bridge. The pneumatic H-bridge has been devised for speed and direction control of the motor. The system characteristics are divided into three main regions, namely low speed, medium speed and high speed. The system is highly non-linear in the low speed region and hence a neuro-modelling approach is proposed.

3

Intelligent methods for active noise and vibration control

Tokhi M. O.

Archives of Acoustics

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2004

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Vol. 29, no. 2

259-273

EN

This paper presents an overview of intelligent soft computing techniques within the framework of active control of noise and vibration. Tools considered include genetic algorithms (GAs), neural networks (NNs) and fuzzy logic (FL). The paper highlights associated merits and potential benefits of the approaches in modelling and control of dynamic systems. These are demonstrated in the control of noise in free-field propagation and vibration suppression in 1D and 2D flexible structures. The paper shows that the potential benefits of the individual components can be exploited and approaches for design and development of hybrid soft-computing algorithms devised for modelling and control of dynamic systems. It is demonstrated that significant benefits in terms of performance can be gained with such hybrid algorithms.

4

Vibration control of pitch movement using command shaping techniques: Experimental investigation

Aldebrez F.M., Tokhi M.O.

Systems Science

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2003

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Vol. 29, nr 2

129-143

EN

This paper investigates the development of feedforward control strategies for vibration control of pitch movement (1 DOF) of a twin rotor multi-input multi-output system (TRMS) using command shaping techniques. Command shaping is a feedforward method used to reduce residual vibrations during motion in flexible systems. The TRMS is a laboratory platform designed for control experiments. In certain aspects, its behaviour resembles that of a helicopter. Feedforward controllers are designed for resonance suppression produced by the main rotor, which produces pitch movement around the longitudinal axis, while the lateral axis (yaw movement) is physically constrained. Three feedforward controllers: input-shaper, low-pass filter and band-stop filter are designed based on the natural frequencies and damping ratios of the system. The three controllers are assessed in terms of level of vibration reduction at the system's natural frequencies. Their performances are compared with an unshaped input (single-switch bang-bang signal) that is used to determine the dynamic response of the system.

5

Genetic algorithms based adaptive active vibration control of a flexible structure

MatDarus I. Z., Tokhi M. O.

Systems Science

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2003

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Vol. 29, nr 3

65-79

EN

This paper investigates the development of an active vibration control (AVC) mechanism for a flexible plate structure using a genetic modelling strategy where the utilisation of genetic algorithms (GAs) for dynamic modelling of the system is considered. The global search technique of GAs is used to obtain a dynamic model of a flexible plate structure based on one-step-ahead (OSA) prediction and verified within the AVC system. The GA based AVC algorithm thus developed is implemented within a flexible plate simulation environment and its performance in the reduction of deflection at the centre of the plate is assessed. The validation of the algorithm is presented in both the time and frequency domains. An assessment of the results thus obtained is given in comparison to the AVC system using conventional recursive least squares (RLS) method. Investigations reveal that the developed GA based AVC system performs better in the suppression of vibration of a flexible plate structure compared to an RLS based AVC system.

6

Adaptive Active Control of Noise and Vibration

Tokhi M.O.

Archives of Control Sciences

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2003

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Vol. 13, no. 2

117-139

EN

This paper presents the development of a unified approach to active control of noise and vibration.The design of an active control system in initially considered on the basis of a singleinput single-output(SISO) structure.The design procedure is formulated so as to allow on-line adaptation and control,and accordingly an adaptive control algorithm is devised.The design is the extended to the case of a single-input multi-output(SIMO)control structure. The control strategies thus devised are verirfied in the cancellation of broadband noise in a free-field medium, and in vibratio suppression in a cantilever beam in fixed-free and fixed-fixed modes.A comparative assessment of the results with SISO and SIMO control structures is presented and discussed.