Add to ORKGAbstract:- In this paper, an evolutionary approach is proposed to obtain a reduced-order discrete interval model for uncertain discrete-time systems having interval uncertainties based on resemblance of discrete sequence energy between the original and reduced systems. System performance of the discrete interval model obtained by using the proposed evolutionary approach is then verified based on time responses of the resulting model in comparison to existing methods to demonstrate the effectiveness of the proposed approach. Key-Words:- Model reduction, discrete-time systems, genetic algorithms, uncertain systems, interval plant
[[abstract]]In this paper, a quantitative index is proposed to address the performance evaluation an...
In recent years, extensive works on genetic algorithms have been reported covering various applicati...
In recent years, extensive works on genetic algorithms have been reported covering various applicati...
[[abstract]]In this paper, an evolutionary approach is proposed to derive a reduced-order model for ...
[[abstract]]A framework to automatically generate a reduced-order discrete-time model for the sample...
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any m...
[[abstract]]A multi-objective genetic algorithm approach is proposed to design tolerance controllers...
[[abstract]]In this paper, a genetic algorithm-based approach is proposed to determine a desired sam...
[[abstract]]In this paper, a genetic algorithm-based approach is proposed to determine a desired sam...
[[abstract]]In this paper, a particle swarm optimization (PSO) based approach is proposed to derive ...
[[abstract]]In this paper, a higher-order integrator approach is proposed to obtain an approximate d...
[[abstract]]Design of a robust controller which stabilizes an interval plant from the signal energy ...
This paper develops a genetic algorithm based technique that may be used to identify multivariable s...
[[abstract]]Design of an optimal controller minimizing the integral of squared error (ISE) of the cl...
proposed a new procedure for modeling of high order linear time invariant SISO Interval systems. The...
[[abstract]]In this paper, a quantitative index is proposed to address the performance evaluation an...
In recent years, extensive works on genetic algorithms have been reported covering various applicati...
In recent years, extensive works on genetic algorithms have been reported covering various applicati...
[[abstract]]In this paper, an evolutionary approach is proposed to derive a reduced-order model for ...
[[abstract]]A framework to automatically generate a reduced-order discrete-time model for the sample...
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any m...
[[abstract]]A multi-objective genetic algorithm approach is proposed to design tolerance controllers...
[[abstract]]In this paper, a genetic algorithm-based approach is proposed to determine a desired sam...
[[abstract]]In this paper, a genetic algorithm-based approach is proposed to determine a desired sam...
[[abstract]]In this paper, a particle swarm optimization (PSO) based approach is proposed to derive ...
[[abstract]]In this paper, a higher-order integrator approach is proposed to obtain an approximate d...
[[abstract]]Design of a robust controller which stabilizes an interval plant from the signal energy ...
This paper develops a genetic algorithm based technique that may be used to identify multivariable s...
[[abstract]]Design of an optimal controller minimizing the integral of squared error (ISE) of the cl...
proposed a new procedure for modeling of high order linear time invariant SISO Interval systems. The...
[[abstract]]In this paper, a quantitative index is proposed to address the performance evaluation an...
In recent years, extensive works on genetic algorithms have been reported covering various applicati...
In recent years, extensive works on genetic algorithms have been reported covering various applicati...