首页|Enhancing modelling accuracy of cascaded spline adaptive filters using the remora optimisation algorithm:application to real-time systems
Enhancing modelling accuracy of cascaded spline adaptive filters using the remora optimisation algorithm:application to real-time systems
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Enhancing modelling accuracy of cascaded spline adaptive filters using the remora optimisation algorithm:application to real-time systems
We first introduce a new approach for optimising a cascaded spline adaptive filter(CSAF)to identify unknown nonlinear systems by using a meta-heuristic optimisation algorithm(MOA).The CSAF architecture combines Hammerstein and Wiener systems,where the nonlinear blocks are implemented with the spline network.The algorithms used optimise the weights of the spline interpolation function and linear filter by using an adequately weighted cost function,leading to improved filter stability,steady state performance,and guaranteed convergence to globally optimal solutions.We investigate two CSAF architectures:Hammerstein-Wiener SAF(HW-SAF)and Wiener-Hammerstein SAF(WH-SAF)structures.These architectures have been designed using gradient-based approaches which are inefficient due to poor convergence speed,and produce suboptimal solutions in a Gaussian noise environment.To avert these difficulties,we estimate the design parameters of the CSAF architecture using four independent MOAs:differential evolution(DE),brainstorm optimisation(BSO),multi-verse optimiser(MVO),and a recently proposed remora optimisation algorithm(ROA).In ROA,the remora factor's control parameters produce near-global optimal parameters with a higher convergence speed.ROA also ensures the most balanced exploration and exploitation phases compared to DE-,BSO-,and MVO-based design approaches.Finally,the identification results of three numerical and industry-specific benchmark systems,including coupled electric drives,a thermic wall,and a continuous stirred tank reactor,are presented to emphasise the effectiveness of the ROA-based CSAF design.
Cascaded spline adaptive filterNonlinear system identificationRemora optimisation algorithm
Lakshminarayana JANJANAM、Suman Kumar SAHA、Rajib KAR
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JNTUK Recognized Research Center,Department of Electronics & Communication Engineering,Sasi Institute of Technology & Engineering,Andhra Pradesh 534101,India
Department of Electronics & Communication Engineering,National Institute of Technology Raipur,Chhattisgarh 492010,India
Department of Electronics & Communication Engineering,National Institute of Technology Durgapur,West Bengal 713209 India
Cascaded spline adaptive filter Nonlinear system identification Remora optimisation algorithm
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