access icon free Data-based predictive control for networked non-linear systems with two-channel packet dropouts

This study is concerned with the data-based control of networked non-linear control systems with random packet dropouts in both the sensor-to-controller and controller-to-actuator channels. By taking advantage of the characteristics of networked control systems such as the packet-based transmission, timestamp technique, as well as smart sensor and actuator, a data-based networked predictive control (DBNPC) method is proposed to actively compensate for the two-channel packet dropouts, where only the input and output data of the non-linear plant are required. A sufficient condition for the stability of the closed-loop system is developed. Furthermore, the resulting DBNPC system can achieve a zero steady-state output tracking error for step commands. Finally, extensive simulation results on a networked non-linear system demonstrate the effectiveness of the proposed method.

Inspec keywords: stability; intelligent sensors; intelligent actuators; closed loop systems; networked control systems; distributed parameter systems; nonlinear control systems; control system synthesis; predictive control

Other keywords: sensor-to-controller channels; data-based networked predictive control method; controller-to-actuator channels; DBNPC system; timestamp technique; step commands; two-channel packet dropouts; design analysis; zero steady-state output tracking error; smart sensor; packet-based transmission; smart actuator; closed-loop system; stability analysis; networked nonlinear control systems

Subjects: Distributed parameter control systems; Stability in control theory; Intelligent sensors; Control system analysis and synthesis methods; Optimal control; Nonlinear control systems; Intelligent actuators

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http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta.2014.0745
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