Control of the technological processes of coal enrichment takes place in the presence of wide disturbances. Thus, one of the basic tasks of the coal enrichment process control systems is the stabilization of coal quality parameters at a preset level. An important problem is the choice of the controller which is robust for a variety of disturbances. The tuning of the controller parameters is no less important in the control process . Many methods of tuning the controller use the dynamic characteristics of the controlled process (dynamic model of the controlled object). Based on many studies it was found that the dynamics of many processes of coal enrichment can be represented by a dynamic model with properties of the inertial element with a time delay. The identification of object parameters (including the time constant) in industrial conditions is usually performed during normal operation (with the influence of disturbances) from this reason, determined parameters of the dynamic model may differ from the parameters of the actual process. The control system with controller parameters tuned on the basis of such a model may not satisfy the assumed control quality requirements. In the paper, the analysis of the influence of changes in object model parameters in the course of the controlled value has been carried out. Research on the controller settings calculated according to parameters T and τ were carried out on objects with other parameter values. In the studies, a sensitivity analysis method was used. The sensitivity analysis for the three methods of tuning the PI controller for the coal enrichment processes control systems characterized by dynamic properties of the inertial element with time delay has been presented. Considerations are performed at various parameters of the object on the basis of the response of the control system for a constant value of set point. The assessment of considered tuning methods based on selected indices of control quality have been implemented.
An on-line optimising control strategy involving a two level extended Kalman filter (EKF) for dynamic model identification and a functional conjugate gradient method for determining optimal operating condition is proposed and applied to a biochemical reactor. The optimiser incorporates the identified model and determines the optimal operating condition while maximising the process performance. This strategy is computationally advantageous as it involves separate estimation of states and process parameters in reduced dimensions. In addition to assisting on-line dynamic optimisation, the estimated time varying uncertain process parameter information can also be useful for continuous monitoring of the process. This strategy ensures that the biochemical reactor is operated at the optimal operation while taking care of the disturbances that are encountered during operation. The simulation results demonstrate the usefulness of the two level EKF assisted dynamic optimizer for on-line optimising control of uncertain nonlinear biochemical systems.
The paper presents a simulation model of the hybrid magnetic bearing dedicated to simulations of transient state. The proposed field-circuit model is composed of two components. The first part constitutes a set of ordinary differential equations that describes electrical circuits and mechanics. The second part of the simulation model consists of parameters such as magnetic forces, dynamic inductances and velocity-induced voltages obtained from the 3D finite element analysis. The MATLAB/Simulnik softwarewas used to implement the simulation model with the required control system. The proposed field-circuit model was validated by comparison of time responses with the prototype of the hybrid magnetic bearing.
The paper presents a model for dynamic analysis of belt transmission. A two dimensional discrete model was assumed of a belt consisting of rigid bodies joined by translational and torsion spring-damping elements. In the model, both a contact model and a dry friction model including creep were taken into consideration for belt-pulley interaction. A model with stiffness and damping between the contacting surfaces was used to describe the contact phenomenon, whereas a simplified model of friction was assumed. Motion of the transmission is triggered under the influence of torque loads applied on the pulleys. Equations of motion of separate elements of the belt and pulleys were solved numerically by using adaptive stepsize integration methods. Calculation results are presented of the reaction forces acting on the belt as well as contact and friction forces between the belt body and pulley in the sample of the belt transmission. These were obtained under the influence of the assumed drive and resistance torques.