Novel Nonlinear Hypothesis for the Delta Parallel Robot Modeling

In previous investigations, the nonlinear hypothesis use the linear bounded maps. Nonlinear hypothesis are described as the combination of the first order terms, and after of the mentioned combination, one bounded map is applied to alter the result. This document proposes two nonlinear hypothesis which use different structures instead of using the linear bounded maps. They are termed as novel nonlinear hypothesis and second order nonlinear hypothesis and their goal is to improve the second order processes modeling. The proposed nonlinear hypothesis are described as the combination of the first order and second order terms. Since the delta parallel robot is a second order process, it is an excellent platform to prove the effectiveness of the two proposed hypothesis.

[1]  Antonio Pescapè,et al.  Distributed detection with fuzzy censoring sensors in the presence of noise uncertainty , 2019, Neurocomputing.

[2]  Maciej Patan,et al.  Neural-network-based iterative learning control of nonlinear systems. , 2020, ISA transactions.

[3]  Yong Chen,et al.  Energy efficient walking control for biped robots using interval type-2 fuzzy logic systems and optimized iteration algorithm. , 2019, ISA transactions.

[4]  Weihua Gui,et al.  A novel deep learning based fault diagnosis approach for chemical process with extended deep belief network. , 2019, ISA transactions.

[5]  Agustín Jiménez,et al.  Multidimensional membership functions in T-S fuzzy models for modelling and identification of nonlinear multivariable systems using genetic algorithms , 2019, Appl. Soft Comput..

[6]  V A Samaranayake,et al.  Direct Error-Driven Learning for Deep Neural Networks With Applications to Big Data , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[7]  Kun Liu,et al.  A fuzzy process neural network model and its application in process signal classification , 2019, Neurocomputing.

[8]  Ju H. Park,et al.  New results for sampled-data control of interval type-2 fuzzy nonlinear systems , 2020, J. Frankl. Inst..

[9]  Zhigang Zeng,et al.  Stabilization of Second-Order Memristive Neural Networks With Mixed Time Delays via Nonreduced Order , 2020, IEEE Transactions on Neural Networks and Learning Systems.

[10]  Zheng Qiumei,et al.  Improved Convolutional Neural Network Based on Fast Exponentially Linear Unit Activation Function , 2019, IEEE Access.

[11]  Xiaohui Yuan,et al.  Fabric Defect Detection Using Activation Layer Embedded Convolutional Neural Network , 2019, IEEE Access.

[12]  Muhammad Ramlee Kamarudin,et al.  A Fuzzy-Based Angle-of-Arrival Estimation System (AES) Using Radiation Pattern Reconfigurable (RPR) Antenna and Modified Gaussian Membership Function , 2019, IEEE Access.

[13]  Lin Xiao,et al.  Design and analysis of three nonlinearly activated ZNN models for solving time-varying linear matrix inequalities in finite time , 2020, Neurocomputing.

[14]  Xiangjian He,et al.  Building an Improved Internet of Things Smart Sensor Network Based on a Three-Phase Methodology , 2019, IEEE Access.

[15]  Wei-Chang Yeh,et al.  A new harmonic continuous simplified swarm optimization , 2019, Appl. Soft Comput..

[16]  Naixue Xiong,et al.  Coronary Arteries Segmentation Based on 3D FCN With Attention Gate and Level Set Function , 2019, IEEE Access.

[17]  Masaki Kobayashi O(2)-Valued Hopfield Neural Networks , 2019, IEEE Trans. Neural Networks Learn. Syst..

[18]  Jing Wang,et al.  A Compact Ciphertext-Policy Attribute-Based Encryption Scheme for the Information-Centric Internet of Things , 2018, IEEE Access.

[19]  Dihua Sun,et al.  Multistability for Almost-Periodic Solutions of Takagi–Sugeno Fuzzy Neural Networks With Nonmonotonic Discontinuous Activation Functions and Time-Varying Delays , 2019, IEEE Transactions on Fuzzy Systems.

[20]  Wei-Chang Yeh,et al.  Solving cold-standby reliability redundancy allocation problems using a new swarm intelligence algorithm , 2019, Appl. Soft Comput..

[21]  Bin Sun,et al.  A New Node-Based Concept for Solving the Minimal Path Problem in General Networks , 2019, IEEE Access.

[22]  Wei-Chang Yeh,et al.  A novel nondominated sorting simplified swarm optimization for multi-stage capacitated facility location problems with multiple quantitative and qualitative objectives , 2019, Appl. Soft Comput..

[23]  Kenli Li,et al.  A robust and fixed-time zeroing neural dynamics for computing time-variant nonlinear equation using a novel nonlinear activation function , 2019, Neurocomputing.

[24]  Cheng-Chew Lim,et al.  Power scheduling optimization under single-valued neutrosophic uncertainty , 2020, Neurocomputing.

[25]  Tien-Loc Le Fuzzy C-Means Clustering Interval Type-2 Cerebellar Model Articulation Neural Network for Medical Data Classification , 2019, IEEE Access.

[26]  S. Meysam Mousavi,et al.  A new soft computing model based on linear assignment and linear programming technique for multidimensional analysis of preference with interval type-2 fuzzy sets , 2019, Appl. Soft Comput..