The LQR (linear quadratic regulator) control problem subject to singular system constitutes a optimization problem in which one must be find an optimal control that satisfy the singular system and simultaneously to optimize the quadratic objective functional. In this paper we establish a sufficient condition to obtain the optimal control of discounted LQR optimization problem subject to disturbanced singular system where the disturbance is time varying. The considered problem is solved by transforming the discounted LQR control problem subject to disturbanced singular system into the normal LQR control problem. Some available results in literatures of the normal LQR control problem be used to find the sufficient conditions for the existence of the optimal control for discounted LQR control problem subject to disturbanced singular system. The final result of this paper is in the form a method to find the optimal control of discounted LQR optimization problem subject to disturbanced singular system. The result shows that the disturbance is vanish with the passage of time.
In a dynamic machining process, distortion in surface irregularity is a very complex phenomenon. Surface irregularities form a periodic representation of the tool profile with various kinds of disturbance in a broad range of changes in the height and length of the profile. To discern these irregularity disturbances, interactions of the tool in the form of changes perpendicular and parallel relative to the workpiece were analyzed and simulated. The individual kinds of displacement of the tool relative to the workpiece introduce distortions in the changes of height and length. These changes are weakly represented in standard height and length irregularity parameters and their discernment has been found through amplitude-frequency functions.
This paper presents a robust control technique for small-scale unmanned helicopters to track predefined trajectories (velocities and heading) in the presence of bounded external disturbances. The controller design is based on the linearized state-space model of the helicopter. The multivariable dynamics of the helicopter is divided into two subsystems, longitudinallateral and heading-heave dynamics respectively. There is no strong coupling between these two subsystems and independent controllers are designed for each subsystem. The external disturbances and model mismatch in the longitudinal-lateral subsystem are present in all (matched and mismatched) channels. This model mismatch and external disturbances are estimated as lumped disturbances using extended disturbance observer and an extended disturbance observer based sliding mode controller is designed for it to counter the effect of these disturbances. In the case of heading-heave subsystem, external disturbances and model mismatch only occur in matched channels so a second order sliding mode controller is designed for it as it is insensitive to matched uncertainties. The control performance is successfully tested in Simulink.
Power quality (PQ) monitoring is important for both the utilities and also the users of electric power. The most widespread measurement instrument used for PQ monitoring is the PQM (Power Quality Monitor) or PQA (Power Quality Analyzer). In this paper we propose the usage of PMU data for PQ parameters monitoring. We present a new methodology of PQ parameters monitoring and classification based on PMU data. The proposed methodology is tested with real measurements performed in distribution system using dedicated PMU system.
The paper presents a research program carried out to improve understanding of the fluid dynamics mechanisms that lead to rotating stall in the axial flow low speed compressor stage. The stalling behavior of this compressor stage was studied by measuring unsteady casing pressure by means of a circumferentially and axially spaced array of high frequency pressure transducers. Another probe used was a disc static pressure probe, with the pressure transducer, for in-flow and out-flow measurements along the blade span. It was expected that understanding of the fluid dynamics will facilitate at least two important tasks. The first was to accurately predict of when and how a particular compressor would stall. The second was to control, delay, or eventually suppress the rotating stall and surge. In consequence, one could extend the useful operating range of the axial compressor. Another motivation for the research was to compare the results from the three applied analysis techniques by using a single stall inception event. The first one was a simple visual inspection of the traces, which brought about a very satisfactory effect. The second one was application of spatial Fourier decomposition to the analysis of stall inception data, and the third method of analysis consisted in application of wavelet filtering in order to better understand the physical mechanisms which lead to rotating stall. It was shown that each of these techniques would provide different information about compressor stall behavior, and each method had unique advantages and limitations.
In this paper an application of extended Kalman filter (EKF) for estimation and attenuation of periodic disturbance in permanent magnet synchronous motor (PMSM) drive is investigated. Most types of disturbances present into PMSM drive were discussed and described. The mathematical model of the plant is presented. Detailed information about the design process of the disturbance estimator was introduced. A state feedback controller (SFC) with feedforward realizes the regulation and disturbance compensation. The theoretical analysis was supported by experimental tests on the laboratory stand. Both time- and frequency-domain analysis of the estimation results and angular velocity were performed. A significant reduction of velocity ripple has been achieved.
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