Frequency domain approach for dynamics identification of the actuator with asymmetric hysteresis

postprin

Parameters Identification for a Composite Piezoelectric Actuator Dynamics

This work presents an approach for identifying the model of a composite piezoelectric (PZT) bimorph actuator dynamics, with the objective of creating a robust model that can be used under various operating conditions. This actuator exhibits nonlinear behavior that can be described using backlash and hysteresis. A linear dynamic model with a damping matrix that incorporates the Bouc–Wen hysteresis model and the backlash operators is developed. This work proposes identifying the actuator’s model parameters using the hybrid master-slave genetic algorithm neural network (HGANN). In this algorithm, the neural network exploits the ability of the genetic algorithm to search globally to optimize its structure, weights, biases and transfer functions to perform time series analysis efficiently. A total of nine datasets (cases) representing three different voltage amplitudes excited at three different frequencies are used to train and validate the model. Four cases are considered for training the NN architecture, connection weights, bias weights and learning rules. The remaining five cases are used to validate the model, which produced results that closely match the experimental ones. The analysis shows that damping parameters are inversely proportional to the excitation frequency. This indicates that the suggested hysteresis model is too general for the PZT model in this work. It also suggests that backlash appears only when dynamic forces become dominant

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

Modeling the Vibrational Dynamics of Piezoelectric Actuator by System Identification Technique

Actuators based on smart materials such as piezoelectric actuators (PEAs) are widely used in many applications to transform electrical signal to mechanical signal and vice versa. However, the major drawbacks for these smart actuators are hysteresis nonlinear, creep and residual vibration. In this paper, PEAs are used for active vibration application. Therefore, a model of PEA must be established to control the vibration that occurs in the system. The frequencies of 1 Hz, 20 Hz and 50 Hz were tested on the PEAs. The results obtained from the experimental were used to develop transfer function model by employing system identification technique. Meanwhile, the model validation was based on level of models fitness to estimation data, mean squared error (MSE), final prediction error (FPE) and correlation test. The experimental result showed that the displacement of the actuator is inversely proportional to the frequency. The following consequences caused the time response criteria at 50 Hz achieved smallest overshoot and fastest response of rise time and settling time

Modelling of servo-controlled pneumatic drives: a generalised approach to pneumatic modelling and applications in servo-drive design

The primary objective of this research is to develop a general modelling facility for modular pneumatic servo-drives. The component-oriented approach has been adopted as the modelling technique to provide the flexibility of modelling a wide variety of components and the segmentation of the non-linear system to less complex uncoupled component modules. A significant part of the research work has been devoted to identify a series of component modules of the single axis linear pneumatic servomechanism with standardised linking variables. The mathematical models have been implemented in a simulation software which produces time domain responses for design evaluation purposes. Alternative components for different servomechanism design were modelled as mutually exclusive modules which could be selected for assembly as if they were real physical entities. The philosophy of the approach was validated by tests on prototype servo-drives with matching components. Design analysis could be performed by simulating and comparing the performance of alternative system structures. [Continues.

Identifikacija bespilotnih ronilica korištenjem postupka vlastitih oscilacija

Control of underwater vehicles is a challenging task since these systems demonstrate highly coupled and nonlinear behavior in uncertain and often unknown environment. In order to successfully design higher levels of control hierarchy, sufficiently accurate parameters of a mathematical model describing the vessel is required. These parameters vary significantly depending on the payload; hence conventional, time-consuming identification methods are tedious. This paper introduces a self-oscillation based method for determining inertia and drag parameters for underwater vehicles. The procedure is easily implementable in field conditions and gives satisfactory results. Both linear and nonlinear models of yaw, heave and surge degree of freedom can be identified. Experimental results obtained from yaw identification experiments on a real underwater vehicle will be presented. In addition to this, the same methodology will be used to determine which model describes the vehicle dynamics more suitably. Modifications of the proposed algorithm for systems with delays and discrete-time systems will be described, together with an estimate of parameter error bounds due to quantization levels.Upravljanje bespilotnim ronilicama predstavlja zahtjevan zadatak budući da ronilice pokazuju snažno spregnuto i nelinearno ponašanje u nepredvidljivim i često nepoznatim okruženjima. U svrhu uspješnog projektiranja viših razina u njihovoj upravljačkoj hijerarhiji, potrebno je dovoljno dobro poznavati parametre matematičkog modela plovila. Ovi se parametri mogu znatno mijenjati ovisno o opremi i drugim uvjetima tijekom misije, stoga su uobičajeni, vremenski zahtjevni identifikacijski postupci neprikladni. Članak opisuje postupak koji koristi vlastite oscilacije za određivanje inercije i otpornosti bespilotnih ronilica. Postupak je lako primjenjiv u terenskim uvjetima i daje zadovoljavajuće rezultate. Linearan i nelinearan model zaošijanja, zaranjanja i napredovanja mogu´ce je identificirati. U radu su prikazani eksperimentalni rezultati dobiveni na identifikacijskim ekperimentima zaošijanja na stvarnoj ronilici. Uz navedeno, ista metodologija je iskorištena za odlučivanje o modelu koji prikladno opisuje stvarnu ronilicu. U radu su opisane i preinake predloženog algoritma za sustave s transportnim kašnjenjem i diskretne sustave, kao i procjene pogrešaka u određivanju parametara koje su posljedica kvantizacije

Robust fractional-order fast terminal sliding mode control with fixed-time reaching law for high-performance nanopositioning

Open Access via the Wiley Agreement ACKNOWLEDGEMENTS This work is supported by the China Scholarship Council under Grant No. 201908410107 and by the National Natural Science Foundation of China under Grant No. 51505133. The authors also thank the anonymous reviewers for their insightful and constructive comments.Peer reviewedPublisher PD

Global fast non-singular terminal sliding-mode control for high-speed nanopositioning

Peer reviewedPostprin