Virtual sensor fusion for high precision control

peer reviewedHigh performance control requires high loop gain and large control bandwidth. However, the spurious resonances at the higher frequencies can limit the performance of such type of systems. This drawback can be overcome by using sensor fusion technique. In sensor fusion, two or more sensors are combined in synergy such that good performance is achieved at lower frequencies while ensuring robustness of the system at higher frequen- cies. This paper presents a new technique, termed as ‘‘virtual sensor fusion”, in which only one of the sensors is physically installed on the system while the other sensor is simulated virtually. The virtual sensor is selected based on desired high frequency response. The effectiveness of the proposed technique is demonstrated numerically for a case of active seismic isolation. A robustness analysis of virtual sensor fusion is also carried out in order to study its stability in the presence of spurious resonances. Finally, the technique is exper- imentally verified on active isolation of pendulum system from ground motion. The results obtained demonstrate good isolation performance at lower frequencies and robustness to plant uncertainties (spurious resonances) at higher frequencies. This technique can be effectively used for high precision control of sensitive instruments

Rotor Position Tracking Control for Low Speed Operation of Direct-Drive PMSM Servo System

In this paper, a rotor position tracking control (RPTC) strategy is proposed to effectively reduce the speed fluctuation for a direct-drive permanent magnet synchronous motor (DD-PMSM) servo system operating at low speed with different torque disturbances. In this strategy, considering the derivative relationship between the rotor position and speed, a speed command is converted to a real-time rotor position trajectory, and then a position-current two-loop control with the RPTC controller is proposed based on the internal model method to smoothly track the rotor position. In addition, the parameter design of RPTC controller from the perspectives of robust stability and anti-disturbance capability is investigated as well. Comparative simulation and experimental results demonstrate that, at low speed, the proposed RPTC strategy has a good speed performance for both periodic and non-periodic torque disturbances. Moreover, it enjoys simple implementation for not requiring the precise speed feedback and specific torque disturbance information

Fault ride-through improvement of DFIG-WT by integrating a two-degrees-of-freedom internal model control

A novel two-degree-of-freedom internal model control (IMC) controller that improves the fault ride-through (FRT) capabilities and crowbar dynamics of doubly fed induction generator (DFIG) wind turbines is presented. As opposed to other control strategies available in the open literature, the proposed IMC controller takes into account the power limit characteristic of the DFIG back-to-back converters and their dc-link voltage response in the event of a fault and consequent crowbar operation. Results from a digital model implemented in Matlab/Simulink and verified by a laboratory scale-down prototype demonstrate the improved DFIG FRT performance with the proposed controller

Internal model control (IMC) approach for designing disk drive servo-controller

10.1109/41.382135IEEE Transactions on Industrial Electronics423248-256ITIE

High performance DSP-based servo drive control for a limited-angle torque motor

This thesis describes the analysis, design and implementation of a high performance DSP-based servo drive for a limited-angle torque motor used in thermal imaging applications. A limited-angle torque motor is an electromagnetic actuator based on the Laws' relay principle, and in the present application the rotation required was from - 10° to + 10° in 16 ms, with a flyback period of 4 ms. To ensure good quality picture reproduction, an exceptionally high linearity of ±0.02 ° was necessary throughout the forward sweep. In addition, the drive voltage to the exciting winding of the motor should be less than the +35 V ceiling of the drive amplifier. A research survey shows that little literature was available, probably due to the commercial sensitivity of many of the applications for torque motors. A detailed mathematical model of the motor drive, including high-order linear dynamics and the significant nonlinear characteristics, was developed to provide an insight into the overall system behaviour. The proposed control scheme uses a multicompensator, multi-loop linear controller, to reshape substantially the motor response characteristic, with a non-linear adaptive gain-scheduled controller to compensate effectively for the nonlinear variations of the motor parameters. The scheme demonstrates that a demanding nonlinear control system may be conveniently analysed and synthesised using frequency-domain methods, and that the design techniques may be reliably applied to similar electro-mechanical systems required to track a repetitive waveform. A prototype drive system was designed, constructed and tested during the course of the research. The drive system comprises a DSP-based digital controller, a linear power amplifier and the feedback signal conditioning circuit necessary for the closed-loop control. A switch-mode amplifier was also built, evaluated and compared with the linear amplifier. It was shown that the overall performance of the linear amplifier was superior to that of the switch-mode amplifier for the present application. The control software was developed using the structured programming method, with the continuous controller converted to digital form using the bilinear transform. The 6- operator was used rather than the z-operator, since it is more advantageous for high speed sampling systems. The gain-scheduled control was implemented by developing a schedule table, which is controlled by the DSP program to update continuously the controller parameters in synchronism with the periodic scanning of the motor. The experimental results show excellent agreement with the simulated results, with linearity of ±0.05 ° achieved throughout the forward sweep. Although this did not quite meet the very demanding specifications due to the limitations of the experimental drive system, it clearly demonstrates the effectiveness of the proposed control scheme. The discrepancies between simulated and experimental results are analyzed and discussed, the control design method is reviewed, and detailed suggestions are presented for further work which may improve the drive performance

Composite Adaptive Internal Model Control: Theory and Applications to Engine Control

To meet customer demands for vehicle performance and to satisfy increasingly stringent emission standard, powertrain control strategies have become more complex and sophisticated. As a result, controller development and calibration have presented a time-consuming and costly challenge to the automotive industry. This thesis aims to develop new control methodologies with reduced calibration effort. Internal model control (IMC) lends itself to automotive applications for its intuitive control structure with simple tuning philosophy. A few applications of IMC to the boost-pressure control problem have been reported, however, none offered an implementable and easy-to-calibrate solution. Motivated by the need to develop robust and easily calibratable control technologies for boost-pressure control of turbocharged gasoline engines, this thesis developed new control design methodologies in the IMC framework. Two directions are pursued: adaptive IMC (AIMC) and nonlinear IMC. A plant model and a plant inverse are explicit components of IMC. In the presence of plant-model uncertainty, combining the IMC structure with parameter identification through the certainty equivalence principle leads to adaptive IMC (AIMC), where the plant model is identified and the plant inverse is derived by inverting the model. We propose the composite AIMC (CAIMC), which identifies the model and the inverse in parallel, and reduces the tracking error through the online identification. ``Composite" refers to the simultaneous identifications. The constraint imposed by the stability of an n-th order model is nonconvex, and it is re-parameterized as a linear matrix inequality. The parameter identification problem with the stability constraint is reformulated as a convex programming problem. Stability proof and asymptotic performance are established for CAIMC of a general n-th order plant. CAIMC is applied to the boost-pressure control problem of a turbocharged gasoline engine. It is first validated on a physics-based high-order and nonlinear proprietary turbocharged gasoline engine Simulink model, and then validated on a turbocharged 2L four-cylinder gasoline engine on a Ford Explorer EcoBoost. Both simulations and experiments show that CAIMC is not only effective, but also drastically reduces the calibration effort compared to the traditional PI controller with feedforward. Nonlinear IMC is presented in the context of the boost-pressure control of a turbocharged gasoline engine. To leverage the available tools for linear IMC design, the quasi-linear parameter varying (quasi-LPV) models are explored. A new approach for nonlinear inversion, referred to as the structured quasi-LPV model inverse, is developed and validated. A fourth-order nonlinear model which sufficiently describes the dynamic behavior of the turbocharged engine is used as the design model, and the IMC controller is derived based on the structured quasi-LPV model inverse. The nonlinear IMC is applicable when the nonlinear system has a special structural property and has not been generalized yet. Simulations on a high-fidelity turbocharged engine model are carried out to show the feasibility of the proposed nonlinear IMC.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136978/1/connieqz_1.pd