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New Design of Neuro - Sliding Mode Control With Chattering Elimination For Twin Rotor MIMO System (TRMS)
| Content Provider | Semantic Scholar |
|---|---|
| Author | Benchaabane, Abbes Boudjemaa, Fabien |
| Copyright Year | 2013 |
| Abstract | In this paper, we will propose a cooperative control approach that is based on the combination of neural network (NN) and the methodology of sliding mode control (SMC) for a twin rotor multi-input multi- output system(TRMS). The TRMS is an experimental aerodynamic test bed representing the control challenges of unmanned aerial vehicles. The main purpose is to overcome the problem of the equivalent control computation and to eliminate the chattering phenomenon. A feed forward neural network (NN) with the learning rule based on sliding mode algorithm is used to assure the calculation of t he equivalent control in the presence of plant uncertainties. The weights of the net are updated such that the corrective control term of Neuro- sliding mode control goes to zero. Simulation results show that the proposed design can successfully adapt to system nonlinearity and complex coupling conditions. It is shown that the proposed control is feasible and effective. Abstract—In this paper, we will propose a cooperative control approach that is based on the combination of neural network (NN) and the methodology of sliding mode control (SMC) for a twin rotor multi-input multi- output system(TRMS). The TRMS is an experimental aerodynamic test bed representing the control challenges of unmanned aerial vehicles. The main purpose is to overcome the problem of the equivalent control computation and to eliminate the chattering phenomenon. A feed forward neural network (NN) with the learning rule based on sliding mode algorithm is used to assure the calculation of t he equivalent control in the presence of plant uncertainties. The weights of the net are updated such that the corrective control term of Neuro- sliding mode control goes to zero. Simulation results show that the proposed design can successfully adapt to system nonlinearity and complex coupling conditions. It is shown that the proposed control is feasible and effective. Abstract—In this paper, we will propose a cooperative control approach that is based on the combination of neural network (NN) and the methodology of sliding mode control (SMC) for a twin rotor multi-input multi- output system(TRMS). The TRMS is an experimental aerodynamic test bed representing the control challenges of unmanned aerial vehicles. The main purpose is to overcome the problem of the equivalent control computation and to eliminate the chattering phenomenon. A feed forward neural network (NN) with the learning rule based on sliding mode algorithm is used to assure the calculation of t he equivalent control in the presence of plant uncertainties. The weights of the net are updated such that the corrective control term of Neuro- sliding mode control goes to zero. Simulation results show that the proposed design can successfully adapt to system nonlinearity and complex coupling conditions. It is shown that the proposed control is feasible and effective. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://manifest.univ-ouargla.dz/documents/Archive/Archive%20Faculte%20des%20Sciences%20et%20Technologies%20et%20des%20Sciences%20de%20le%20Matiere/The-INTERNATIONAL-CONFERENCE-ON-ELECTRONICS-OIL-FROM-THEORY-TO-APPLICATIONS2013/A_BENCHAABANE.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
