2017
DOI: 10.15282/jmes.11.4.2017.23.0289
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Second order sliding mode control for direct drive positioning system

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Cited by 9 publications
(5 citation statements)
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“…Furthermore, the transient response of each configuration was analyzed using seven parameters to determine the performance of each controller. The parameters included rise time, settling time, overshoot, mean pressure value, root mean square error (RMSE), and maximum spike [23], [24]. In terms of the feedback system, the pressure values were obtained by the sensor for each controller every second.…”
Section: Control System Configurationmentioning
confidence: 99%
“…Furthermore, the transient response of each configuration was analyzed using seven parameters to determine the performance of each controller. The parameters included rise time, settling time, overshoot, mean pressure value, root mean square error (RMSE), and maximum spike [23], [24]. In terms of the feedback system, the pressure values were obtained by the sensor for each controller every second.…”
Section: Control System Configurationmentioning
confidence: 99%
“…It has a special application on the different nonlinear systems based on feedback linearization by the use of nonlinear feedback law it would able to compute required torque in the arm [15][16][17][18]. It performs significantly well when all dynamic and physical parameter of the system is known [19][20][21][22][23]. The CTC like control appears in Robust, Adaptive and Learning Control [19,23,24].…”
Section: Control: Computed Torque Controller Analysismentioning
confidence: 99%
“…It performs significantly well when all dynamic and physical parameter of the system is known [19][20][21][22][23]. The CTC like control appears in Robust, Adaptive and Learning Control [19,23,24]. Figure 3 provides the block diagram for PD-CTC Controller, which illustrates that it's a feedback control system.…”
Section: Control: Computed Torque Controller Analysismentioning
confidence: 99%
“…In spite of linear fixed parameters PID controllers are often suitable for controlling a simple physical process, the demands for high performance control with different operating point conditions or environmental parameters are often beyond the abilities of simple PID controllers. It can improve the performance of linear PID controllers using several techniques which will be established to increase the flexibility and robustness for instance, the self-tuning method, general predictive control, neural networks strategy and fuzzy logic, and other methods [24].…”
Section: Identified Model (Nonlinear Arx Model)mentioning
confidence: 99%