Active Disturbance Rejection Control of Certain Balanced and Positioning Electro-Hydraulic Servo System Based on Neural Network
For certain balance and positioning of electro-hydraulic servo system existing nonlinear, the active disturbance rejection control (ADRC) has many adjustable parameters which are difficult to regulate, so active disturbance rejection control with neural network (NN-ADRC) is developed in this paper. The method uses neural network self-learning ability, through a single neuron adaptive configuration parameters to complete an online self-tuning parameters, while taking advantage of RBF neural network as identifier to identify the controlled object gradient information. Simulation results show that: the controller parameters are reduced significantly, and effectively inhibit the system unbalance force disturbance and realize the accurate positioning. It also has fast response speed, no overshoot, and high steady-state accuracy.
A novel active disturbance rejection-based control strategy for a gun control system
To compensate for the nonlinearity and to achieve finely-tuned tracking accuracy of a gun control system driven by an AC machine, an improved active disturbance rejection control (IADRC) strategy with neural network embedding (NN-IADRC) is developed in this paper. The proposed IADRC, which has amnestic memory effects, can be regarded as an extension of the conventional ADRC (CADRC), making it a special case of the IADRC. To further attenuate the dependence on system models and enhance the disturbance rejection capacities of the IADRC strategy, an on-line NN-based optimum updating approach is also developed in this paper. Finally, a series of experiments are conducted on the semi-physical simulation platform to estimate the performance of the control system and the effects of the memory factor on the system. The experimental results confirm that the proposed NN-IADRC is highly robust. The results also confirm that it performs more excellently than the CADRC and that its fine tuning has attained tracking accuracy.
The Application of Fractional Order Control to Backlash Vibration Suppression
This paper applies fractional order PID k con- troller to torsional system's backlash vibration suppression control, in which the order k of D controller can not only be integer but also be any real number. In order to improve control system's robustness against backlash non-linearity, several methods have been proposed. However their design processes are very complicated. In this paper, a clear and straightforward design is achieved by adjusting the D con- troller's order k directly. An approximation method based on sampling time scaling property is also introduced to realize the discrete D k controller. Design process and experimental results demonstrate straightforward robust control design through the novel Fractional Order Control (FOC) approach, the PID k control system's robustness against backlash non-linearity and good approximation of the realization method.