It has been consistently demonstrated that initial exertion of self-control had negative influence on people's performance on subsequent self-control tasks. This phenomenon is referred to as the ego depletion effect. Based on action control theory, the current research investigated whether the ego depletion effect could be moderated by individuals' action versus state orientation. Our results showed that only state-oriented individuals exhibited ego depletion. For individuals with action orientation, however, their performance was not influenced by initial exertion of self-control. The beneficial effect of action orientation against ego depletion in our experiment results from its facilitation for adapting to the depleting task.
The precise motion control of a hydraulic motor system has some problems due to uncertain disturbance, complex nonlinear dynamics. Traditional methods are difficult to obtain the desired control performance. In this paper, a new fuzzy neural network (FNN) combined with terminal sling mode control (TSMC) and time delay estimation (TDE) is proposed. FNN is used to adjust the parameter of TSMC to reduce the time for the system to reach the equilibrium point and chatting. To increase the accuracy of the system, TDE is used to compensate the error caused by uncertain disturbance. This controller was simulated in Amesim and Simulink, and the results showed that the control scheme proposed in this paper has the smallest angular displacement error, angular velocity error and variance than other control schemes, such as PID and sliding mode control (SMC). Furthermore, the designed controller was implemented on a drill pipe automatic handling manipulator, and its control performance was verified.
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