The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In the paper an application of IMC structure for electric drive with variable mechanical parameters is presented. The mechanical parameters changing as a function of motor shaft angle. The control system was used a neural inverse model trained on line by the modified algorithm RPROP. The collected results of simulation and experiment confirm the proper operation of the control system.
Voice coil motor (VCM) is one of the linear electric machine which has faster transient response, higher accuracy. It is widely used in the field of high performance direct drive servo valve. The mathematic model of voice coil motor was analyzed and the position control system of direct driver valve that based on voice coil motor was designed. Against the disturbance in the system, a new position...
A multivariate self-adapting decoupling control method based on CMAC and PID was proposed in this paper. The control strategy utilizes PID controller and CMAC to combine a composite controller. Using the composite controller, the strong coupled time-varying system can be decoupled and controlled easily. The doubly fed hydro-generator system is a novel type of hydraulic generation system. Considering...
A fuzzy-neuro controller has been designed to stabilize the frequency and voltage output of a synchronous generator. The structure of the proposed control system consists of two PI -like fuzzy controllers and two neural networks. With this control scheme, difficulty for tuning scale factors of the fuzzy controller is reduced. Simulation results show that the system is robust to drastic changes on...
Large-scale Generating Unit in heat power is a system which is complex nonlinear, multivariable, time-variant with long-time delay and difficult to establish accurate model, and etc. So it is hard to make system gain optimum running effect with conventional control strategy. A PID network which has dynamic character is used to identify the coordinated control system for establishing a predictive model...
PID control systems are widely used in many fields, and many methods to tune parameters of PID controller are known. When the characteristics of the object are changed, the traditional PID control should be adjusted by empirical knowledge. It may bring a worse performance to the system. In this paper, a new method to tune PID parameters called as the modified back propagate network by particle swarm...
In this paper, a self-tuning control of a two-link flexible manipulator using neural networks is presented. The neural networks learn the gains of PI controllers for the flexible manipulator. Numerical results show that this presented neural network control system can suppress the vibration of the flexible manipulator and track the desired joint angles. Simulation results show that the self-tuning...
This paper presents an artificial neural network (ANN) controller for automatic generation control of a two area hydro-electric power system. A hierarchical architecture of three layer feed forward neural network (NN) is proposed for controller design, two networks are used, one for identifying the system and other for control respectively, trained based on back propagation algorithm (BPA). The regulator...
This paper proposes a method for fuzzy gain scheduling state-space model predictive controller to deal with the nonlinearity of the boiler-turbine system. Simulation results over wide range show the good load-tracking property and robust control performance of the proposed controller under amplitude and slew-rate constraints on the manipulated variables.
In this paper, a recurrent artificial neural network (RNN) based self-tuning speed controller is proposed for the high-performance drives of induction motors. The RNN provides a nonlinear modeling of a motor drive system and could provide the controller with information regarding the load variation, system noise, and parameter variation of the induction motor through the online estimated weights of...
This paper is concerned with high performance control of three-phase UPS system. The basic requirements of a UPS control system are mentioned. Different control techniques are classified and their performance is briefly described. A hybrid learning-adaptive controller is proposed based on the performance of existing methods. For the learning part, a Repetitive Controller (RC) is used and a Model Reference...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.