Title | ||
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Indirect Neuroadaptive Control Design for High-order Nonlinear MIMO Systems with Actuator Failures |
Abstract | ||
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The paper focus on its unknown trajectory concluding uncertain dynamics, sensor failures and even unanticipated actuator faults. Introducing a speed function, this work puts forward an indirect adaptive neural network control protocol which is adopted to achieve the object that the uncertain MIMO nonlinear systems tracks the unknown trajectory. We, to be specific, purposes a model to link estimated target trajectory with the actual hidden one mathematically. Similarly, we have the relationship between the predicted and the polluted. It is shown that the instantaneous behaviour of the tracking process during the main course of the system operation is improved and all the signals are uniformly ultimately bounded. The numerical simulation examples are taken advantage to expound the effectiveness of controller design scheme in this work. |
Year | DOI | Venue |
---|---|---|
2018 | 10.1109/ICARCV.2018.8581258 | 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) |
Keywords | Field | DocType |
Adaptive control,uncertain target,actuation faults,speed function,UUB | Mimo systems,Nonlinear system,Computer simulation,Computer science,Control theory,Control engineering,Adaptive control,Artificial neural network,Trajectory,Actuator,Bounded function | Conference |
ISSN | ISBN | Citations |
2474-2953 | 978-1-5386-9583-8 | 0 |
PageRank | References | Authors |
0.34 | 6 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Rui Gao | 1 | 23 | 6.42 |
Jiangshuai Huang | 2 | 386 | 18.80 |
Jiawei Chen | 3 | 58 | 11.22 |
Fangzheng Xue | 4 | 0 | 0.68 |