Comparison of different repetitive control architectures: synthesis and comparison. Application to VSI Converters

Repetitive control is one of the most used control approaches to deal with periodic references/disturbances. It owes its properties to the inclusion of an internal model in the controller that corresponds to a periodic signal generator. However, there exist many different ways to include this internal model. This work presents a description of the different schemes by means of which repetitive control can be implemented. A complete analytic analysis and comparison is performed together with controller synthesis guidance. The voltage source inverter controller experimental results are included to illustrative conceptual developmentsPeer ReviewedPostprint (published version

Performance-driven control of nano-motion systems

The performance of high-precision mechatronic systems is subject to ever increasing demands regarding speed and accuracy. To meet these demands, new actuator drivers, sensor signal processing and control algorithms have to be derived. The state-of-the-art scientific developments in these research directions can significantly improve the performance of high-precision systems. However, translation of the scientific developments to usable technology is often non-trivial. To improve the performance of high-precision systems and to bridge the gap between science and technology, a performance-driven control approach has been developed. First, the main performance limiting factor (PLF) is identified. Then, a model-based compensation method is developed for the identified PLF. Experimental validation shows the performance improvement and reveals the next PLF to which the same procedure is applied. The compensation method can relate to the actuator driver, the sensor system or the control algorithm. In this thesis, the focus is on nano-motion systems that are driven by piezo actuators and/or use encoder sensors. Nano-motion systems are defined as the class of systems that require velocities ranging from nanometers per second to millimeters per second with a (sub)nanometer resolution. The main PLFs of such systems are the actuator driver, hysteresis, stick-slip effects, repetitive disturbances, coupling between degrees-of-freedom (DOFs), geometric nonlinearities and quantization errors. The developed approach is applied to three illustrative experimental cases that exhibit the above mentioned PLFs. The cases include a nano-motion stage driven by a walking piezo actuator, a metrological AFM and an encoder system. The contributions of this thesis relate to modeling, actuation driver development, control synthesis and encoder sensor signal processing. In particular, dynamic models are derived of the bimorph piezo legs of the walking piezo actuator and of the nano-motion stage with the walking piezo actuator containing the switching actuation principle, stick-slip effects and contact dynamics. Subsequently, a model-based optimization is performed to obtain optimal drive waveforms for a constant stage velocity. Both the walking piezo actuator and the AFM case exhibit repetitive disturbances with a non-constant period-time, for which dedicated repetitive control methods are developed. Furthermore, control algorithms have been developed to cope with the present coupling between and hysteresis in the different axes of the AFM. Finally, sensor signal processing algorithms have been developed to cope with the quantization effects and encoder imperfections in optical incremental encoders. The application of the performance-driven control approach to the different cases shows that the different identified PLFs can be successfully modeled and compensated for. The experiments show that the performance-driven control approach can largely improve the performance of nano-motion systems with piezo actuators and/or encoder sensors

Computer hardware and software for robotic control

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems

Linear motor motion control using a learning feedforward controller

The design and realization of an online learning motion controller for a linear motor is presented, and its usefulness is evaluated. The controller consists of two components: (1) a model-based feedback component, and (2) a learning feedforward component. The feedback component is designed on the basis of a simple second-order linear model, which is known to have structural errors. In the design, an emphasis is placed on robustness. The learning feedforward component is a neural-network-based controller, comprised of a one-hidden-layer structure with second-order B-spline basis functions. Simulations and experimental evaluations show that, with little effort, a high-performance motion system can be obtained with this approach

Analysis and design of robust stabilizing modified repetitive control systems

In control system practice, high precision tracking or attenuation for periodic signals is an important issue. Repetitive control is known as an e.ective approach for such control problems. The internal model principle shows that the repetitive control system which contains a periodic generator in the closed-loop can achieve zero steady-state error for reference input or completely attenuate disturbance. Due to its simple structure and high control precision, repetitive control has been widely applied in many systems. To improve existing results on repetitive control theory, this thesis presents theoretical results in analysis and design repetitive control system. The main work and innovations are listed as follows: We propose a design method of robust stabilizing modi.ed repetitive controllers for multiple-input/multiple-output plants with uncertainties. The parameterization of all robust stabilizing modi.ed repetitive controllers for multiple-input/multiple-output plant with uncertainty is obtained by employing H∞ control theory based on the Riccati equation. The robust stabilizing controller contains free parameters that are designed to achieve desirable control characteristic. In addition, the bandwidth of low-pass .lter has been analyzed. In order to simplify the design process and avoid the wrong results obtained by graphical method, the robust stability conditions are converted to LMIs-constraint conditions by employing the delay-dependent bounded real lemma. When the free parameters of the parameterization of all robust stabiliz-ing controllers is adequately chosen, then the controller works as robust stabilizing modi.ed repetitive controller. For a time-varying periodic disturbances, we give an design method of an opti-mal robust stabilizing modi.ed repetitive controller for a strictly proper plant with time-varying uncertainties. A modi.ed repetitive controller with time-varying delay structure, inserted by a low-pass .lter and an adjustable parameter, is developed for this class of system. Two linear matrix inequalities LMIs-based robust stability con-ditions of the closed-loop system with time-varying state delay are derived for .xed parameters. One is a delay-dependent robust stability condition that is derived based on the free-weight matrix. The other robust stability condition is obtained based on the H∞ control problem by introducing a linear unitary operator. To obtain the desired controller, the design problems are converted to two LMI-constrained opti-mization problems by reformulating the LMIs given in the robust stability conditions. The validity of the proposed method is verified through a numerical example.学位記番号：工博甲46

Measurements, Models, Systems and Design

531 s.