Boomipalagan Kaviarasan

According to our database1, Boomipalagan Kaviarasan authored at least 30 papers between 2015 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


Online presence:



Fault Estimation for Mode-Dependent IT2 Fuzzy Systems With Quantized Output Signals.
IEEE Trans. Fuzzy Syst., 2021

Stochastic faulty estimator-based non-fragile tracking controller for multi-agent systems with communication delay.
Appl. Math. Comput., 2021

Modified Repetitive Control Design for Nonlinear Systems With Time Delay Based on T-S Fuzzy Model.
IEEE Trans. Syst. Man Cybern. Syst., 2020

Non-fragile control protocol for finite-time consensus of stochastic multi-agent systems with input time-varying delay.
Int. J. Mach. Learn. Cybern., 2020

Faulty actuator-based control synthesis for interval type-2 fuzzy systems via memory state feedback approach.
Int. J. Syst. Sci., 2020

Finite-time boundedness of interval type-2 fuzzy systems with time delay and actuator faults.
J. Frankl. Inst., 2019

Finite-time leaderless consensus of uncertain multi-agent systems against time-varying actuator faults.
Neurocomputing, 2019

Finite-time consensus of input delayed multi-agent systems via non-fragile controller subject to switching topology.
Neurocomputing, 2019

Non-fragile control design for interval-valued fuzzy systems against nonlinear actuator faults.
Fuzzy Sets Syst., 2019

Observer and Stochastic Faulty Actuator-Based Reliable Consensus Protocol for Multiagent System.
IEEE Trans. Syst. Man Cybern. Syst., 2018

Non-fragile filtering for singular Markovian jump systems with missing measurements.
Signal Process., 2018

Resilient sampled-data control design for singular networked systems with random missing data.
J. Frankl. Inst., 2018

Leader-following exponential consensus of input saturated stochastic multi-agent systems with Markov jump parameters.
Neurocomputing, 2018

Resilient control design for consensus of nonlinear multi-agent systems with switching topology and randomly varying communication delays.
Neurocomputing, 2018

Finite-Time Nonfragile Synchronization of Stochastic Complex Dynamical Networks with Semi-Markov Switching Outer Coupling.
Complex., 2018

Finite-time fault-tolerant control of neutral systems against actuator saturation and nonlinear actuator faults.
Appl. Math. Comput., 2018

Dissipative analysis for network-based singular systems with non-fragile controller and event-triggered sampling scheme.
J. Frankl. Inst., 2017

Finite-time dissipative based fault-tolerant control of Takagi-Sugeno fuzzy systems in a network environment.
J. Frankl. Inst., 2017

Finite-time mixed H∞ and passive filtering for Takagi-Sugeno fuzzy nonhomogeneous Markovian jump systems.
Int. J. Syst. Sci., 2017

Synchronization and state estimation for stochastic complex networks with uncertain inner coupling.
Neurocomputing, 2017

Reliable state estimation of switched neutral system with nonlinear actuator faults via sampled-data control.
Appl. Math. Comput., 2017

Reliable dissipative control of high-speed train with probabilistic time-varying delays.
Int. J. Syst. Sci., 2016

Synchronization of complex dynamical networks with uncertain inner coupling and successive delays based on passivity theory.
Neurocomputing, 2016

Robust reliable <i>L</i><sub>2</sub> - <i>L<sub>∞</sub></i> control for continuous-time systems with nonlinear actuator failures.
Complex., 2016

Sampled-data reliable stabilization of T-S fuzzy systems and its application.
Complex., 2016

Robust consensus of nonlinear multi-agent systems via reliable control with probabilistic time delay.
Complex., 2016

Dissipativity based repetitive control for switched stochastic dynamical systems.
Appl. Math. Comput., 2016

Synchronization of singular Markovian jumping complex networks with additive time-varying delays via pinning control.
J. Frankl. Inst., 2015

Leader-following consensus for networked multi-teleoperator systems via stochastic sampled-data control.
Neurocomputing, 2015

Leader-following consensus of multi-agent systems via sampled-data control with randomly missing data.
Neurocomputing, 2015