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.
Accurate measurements of output characteristics and detonations of motorbike high-speed racing engine and their optimization at actual atmospheric conditions and combusted mixture composition
Abstract At a motorbike high speed racing engine there is very important an output engine characteristics which depends significantly on a detonation combustion rate, atmospheric conditions and a combusted mixture composition. The combustion process has got a relevant influence on a wear degree of main engine parts or on their damage eventually. The detonation combustion rate is very important because this kind of burning can be not only destructive but a useful phenomenon, as well. If the process of detonation burning is kept on a certain level, it can help significantly to the next increasing of an engine power output. In this article there is described the measurements of output characteristics of a high-speed racing engine which were performed by means of a data-recording system and the detonation combustion was evaluated using a quantitative method. The actual values of atmospheric conditions and the mixture composition were added to the measured values. Then the obtained values are compared visually with a damage degree of an engine piston caused by the detonation burning. The result is a limit value expressed in a number of detonation units related to a run distance interval of the vehicle driven by the high-speed racing engine. In framework of this run distance interval there is the process of detonation burning profitable. As well as it increases an engine power output and together it is not destructive with regard to engine design parts.