System Identification Experiments Research Articles

Reduced-order model-inspired experimental identification of damped nonlinear structures

In this work, we address Nonlinear System Identification (NSI) of geometrically nonlinear structures using experimental response data. Specifically we consider nonlinear structures with large inertia effects. A laboratory scale cantilever-type beam structure is considered, which is chosen for its large inertial effects. Free decay data is gathered from the experimental cantilever-type beam system using an image-based measurement technique. A general mathematical model is derived for nonlinear systems with large inertia, by taking inspiration from model reduction methods. Specifically, a reduced-order modelling method, which accounts for the kinetic energy of the modes not included in the reduction basis, is utilised for experimental NSI. Experimental system identification using the ROM-inspired model shows superior accuracy compared to standard stiffness nonlinear models typically used for modelling such systems. We also identify the damping of the structure by projecting the effect of unmodelled modes onto non-conservative dissipative forces in the ROM-inspired model. We show that this addresses issues of poor fit associated with using a linear damping model. This results in a nonlinear damping force in the ROM-inspired model which accounts for the damping effect of the unmodelled modes. These nonconservative effects of unmodelled modes are often neglected, which results in an incorrect damping estimation. A crude Finite-Element (FE) model of the cantilever-type beam is used to generate the nonlinear mapping of nonlinear damping force. The free decay response of the identified nonconservative ROM-inspired model closely matches the measurement decay response. This further validates the accuracy of the ROM-inspired model in NSI.

Research on an Active Adjustment Mechanism Based on Non-Singular Terminal Sliding Mode and Finite-Time Disturbance Observer

With the continuous development of synchrotron radiation light sources, higher requirements have been put forward for the stability of double-crystal monochromators in synchrotron radiation facilities. This paper designs an active adjustment mechanism for a double-crystal monochromator to improve its stability. Firstly, three spatial degrees of freedom are designed based on the active adjustment mechanism of flexible leaf spring parallel coupling, and the prototype of the mechanism is fabricated. Secondly, system identification experiments are carried out and the system transfer function curve is fitted by the nonlinear least squares method. Thirdly, the controller based on non-singular terminal sliding modes and a finite-time disturbance observer was designed for stability control and disturbance compensation. Finally, the effectiveness of the controller is verified by a model-in-the-loop approach based on the performance of the real-time target machine. The results show that the non-singular terminal sliding mode + finite-time disturbance observer control strategy can reduce the RMS value of the vibration displacement of Axis-1/Axis-2/Axis-3 by 81.25%, 78.53%, and 71.82%.

Linear Motor System Identification and Simulation Experiments Based on LabVIEW

Linear Motor System Identification and Simulation Experiments Based on LabVIEW

Development of real-time density feedback control on MAST-U in L-mode

In this paper we report on the development and demonstration of density feedback control for MAST-U. Sinusoidal perturbations are used to measure the frequency response from a deuterium gas valve (actuator) to line-integrated core electron density measured by the interferometer (sensor). In the frequency range relevant for control design, only two system-identification experiments were needed to regress a first-order dynamic model. This control-oriented model informs the offline design of a proportional integral controller with the established loop-shaping controller design method. After offline verification of the controller implementation, control is demonstrated by experimentally tracking a staircase reference for the line-integrated electron density. This paper demonstrates the efficiency of controller design using system-identification and loop-shaping, providing reliable density control for MAST-U.

Force tracking control for hydraulically actuated adaptive high-rise buildings

Adaptive high-rise buildings comprise sensors, a control unit and actuators and are able to actively compensate disturbances, allowing the realization of significantly lighter structures compared to conventional constructions. This publication presents the development of a force tracking controller for hydraulic actuators on adaptive high-rise buildings. First, nonlinear models of a single- and a double-acting hydraulic cylinder, used for two different ways of actuation in the structure, are derived. The characteristic curve for the valve cross-section is determined through experimental system identification. Second, a flatness-based input/output linearization is applied to both actuator models. A gain scheduling algorithm sets the proportional gain of the force tracking controller based on a measure reflecting the dynamics of the reference signal and thus avoiding control spillover due to mechanical coupling between the actuator and the structure. The force tracking controller is tested experimentally on the worldwide first adaptive building and its tracking behavior is analyzed based on the cutoff frequency of the closed loop system.

Attitude modelling and real-time robust control of a 3-DoF quadcopter UAV test bench

Abstract In this work, a three degrees-of-freedom (3-DoF) static quadcopter unmanned aerial vehicle (UAV) test-rig of a pendulum-type configuration is custom-designed, developed, instrumented, and interfaced with a PC. The rig serves as a test bed to develop high-fidelity mathematical models as well as to investigate autopilot designs and real-time closed-loop controllers’ performances. The Simulink Desktop Real-Time software is employed for the quadcopter’s attitude signals acquisition and real-time implementation of closed-loop controllers on a target microcontroller hardware. The mathematical models for pitch, roll, and yaw axes are derived via the first principle and validated with the experimental linear system identification (SI) techniques. Subsequently, employing the multi-parameter root contour technique, the classical proportional integral derivative (PID) controllers are designed and implemented in real-time on the quadcopter UAV test rig. This served as a benchmark controller for comparing it with an integral-based linear quadratic regulator (LQR) controller. Further, to improve the transient response of the LQR controller, a novel robust integral-based LQR controller with a feedforward term (LQR-FF) is implemented, which shows much superior performance than the benchmark and basic LQR controller. This work thus will act as a precursor for a more complex 3-DoF autopilot design of an untethered quadcopter.

Experimental graybox quantum system identification and control

Understanding and controlling engineered quantum systems is key to developing practical quantum technology. However, given the current technological limitations, such as fabrication imperfections and environmental noise, this is not always possible. To address these issues, a great deal of theoretical and numerical methods for quantum system identification and control have been developed. These methods range from traditional curve fittings, which are limited by the accuracy of the model that describes the system, to machine learning (ML) methods, which provide efficient control solutions but no control beyond the output of the model, nor insights into the underlying physical process. Here we experimentally demonstrate a ‘graybox’ approach to construct a physical model of a quantum system and use it to design optimal control. We report superior performance over model fitting, while generating unitaries and Hamiltonians, which are quantities not available from the structure of standard supervised ML models. Our approach combines physics principles with high-accuracy ML and is effective with any problem where the required controlled quantities cannot be directly measured in experiments. This method naturally extends to time-dependent and open quantum systems, with applications in quantum noise spectroscopy and cancellation.

Experimental admittance-based system identification for equivalent circuit modeling of piezoelectric energy harvesters on a plate

Equivalent circuit modeling is a useful tool for piezoelectric energy harvesters to analyze the electromechanical response of the system especially when complex host structure geometries and nonlinear circuits are used in the harvesting systems. Previous studies have used analytical and finite element models to estimate the equivalent circuit model (ECM) of piezoelectric energy harvesters (PEH) on beam- and plate-like structures. However, those methods require accurate analytical and/or numerical representation of the PEH. Here, we present an experimental admittance-based system identification method that allows us to identify the multi-modal ECM without prior knowledge of the host plate's geometry and/or physical properties of the piezoelectric patches. Using the proposed experimental method, we obtain the electromechanical frequency–response admittance of the PEH system at each vibration mode, and thereby, we calculate the equivalent system parameters. Additionally, a novel experimental technique is presented for the identification of the equivalent voltage sources associated with each LCR branch of the ECM. The derived ECM is experimentally validated for single and multiple piezoelectric patch harvesters on a plate. The electrical frequency response of the system has been validated for standard AC and rectifier circuits using SPICE software. Overall, the proposed admittance-based system identification is an accurate and robust method to identify the equivalent system parameters, making it a practical and reliable tool for modeling piezoelectric energy harvesting systems.

Parameter identification and position control for helical hydraulic rotary actuators based on particle swarm optimization

It is difficult to obtain an accurate mathematical model in electro-hydraulic servo control system, due to the nonlinear factors such as dead zone, saturation, flow coefficient, and friction. Hence, a parameter identification algorithm, combining recursive least squares (RLS) with modified nonlinear particle swarm optimization (NPSO) algorithm, is proposed. On this basis, another improved NPSO algorithm is also put forward, aiming at searching for the optimal proportional–integral (PI) controller gain of the nonlinear hydraulic system while giving comprehensive consideration to the system performance indexes. The system identification experiments and position tracking control are conducted, respectively. As indicated by the comparison with the least squares (LS), RLS, PSO, and RLS–LPSO results, the proposed method shows higher identification and control accuracy.

FeelPen: A Haptic Stylus Displaying Multimodal Texture Feels on Touchscreens

The ever-emerging mobile market induced a blooming interest in stylus-based interactions. Most state-of-the-art styluses either provide no haptic feedback or only deliver one type of sensation, such as vibration or skin stretch. Improving these devices with display abilities of a palette of tactile feels can pave the way for rendering realistic surface sensations, resulting in more natural virtual experiences. However, integrating necessary actuators and sensors while keeping the compact form factor of a stylus for comfortable user interactions challenges their design. This situation also limits the scientific knowledge of relevant parameters for rendering compelling artificial textures for stylus-based interactions. To address these challenges, we developed FeelPen, a haptic stylus that can display multimodal texture properties (compliance, roughness, friction, and temperature) on touchscreens. We validated the texture rendering capability of our design by conducting system identification and psychophysical experiments. The experimental results confirmed that FeelPen could render a variety of modalities with wide parameter ranges necessary to create perceptually salient texture feels, making it a one-of-a-kind stylus. Our unique design and experimental results pave the way for new perspectives with stylus-based interactions on future touchscreens.

Targeting a Versatile Actuator for EU-DEMO: Real Time Monitoring of Pellet Delivery to Facilitate Burn Control

Core particle fueling, an essential task in the European demonstration fusion power plant EU-DEMO, relies on adequate pellet injection. However, pellets are fragile objects, and their delivery efficiency can hardly be assumed to be unity. Exploring kinetic control of the EU-DEMO1 scenario indicates that such missed-out pellets do cause a considerable problem for keeping a burning plasma. Missed-out pellets can cause a severe drop of plasma density that in turn results in a potential drastic loss of burn power. Efforts are under way at the ASDEX Upgrade (AUG) tokamak aiming to provide real-time monitoring of pellet arrival and announcement of missed-out cases to the control systems. To further optimize the controllers, system identification experiments have been performed to identify the dynamic response of the system to the actuators.

Nonlinear adaptive sliding mode control with application to quadcopters

AbstractNonlinear adaptive sliding mode control (NASMC) has the capability to adequately control a system whose parameters are unknown to the controller designer. Conventional model-based controllers require a mathematical dynamic model of the system with known parameters. These system parameters are normally determined by extensive system identification experiments, which are expensive and time-consuming to perform. A NASMC approach that does not require known system parameters is proposed. Using NASMC, a controller designer can skip the expensive and time-consuming system parameter identification and fast-forward to the control implementation. In addition, once a controller is derived for a quadcopter using NASMC, the same controller will work on any quadcopter with the same equations of motion but different dynamic parameters. The formulation of the NASMC is presented for general second-order and fourth-order systems. Then, as an implementation example, the application of the general NASMC approach is demonstrated by applying it to a quadcopter unmanned aerial vehicle in simulation.

Experimental assessment and validation of energy-maximising moment-based optimal control for a prototype wave energy converter

In recent years, a framework for control of wave energy converters (WECs), termed moment-based control, has been developed within the wave energy conversion literature, exhibiting a remarkable performance in terms of energy absorption, while retaining real-time computational capabilities. Nonetheless, to date, practical results regarding moment-based control for WEC systems have been exclusively provided in numerical simulation, i.e. there is currently a lack of ‘real-world’ assessment of this promising control framework. Motivated by this, we present, in this paper, an experimental assessment and validation of moment-based WEC control for a prototype Wavestar wave energy converter, at the tank-testing facilities of Aalborg University, Denmark. In particular, we address the control design and synthesis procedure in an integrated fashion, covering experimental (physically consistent) system identification, unknown-input estimation and forecasting of wave excitation force, and subsequent control law implementation. We demonstrate that the moment-based controller is able to effectively maximise energy absorption from the wave resource in real-time, with a significant and consistent improvement with respect to the defined benchmark case. The results presented and discussed in this paper demonstrate the feasibility of moment-based WEC control, filling the gap between the attractive theoretical aspects associated with such a strategy, and the practical WEC energy conversion application.

Disturbance rejection enhancement using predictive control for the fixed‐wing UAV with multiple ailerons

SummaryThe performance of small fixed‐wing unmanned aerial vehicles (UAVs) is easily degraded by exogenous disturbances. In an attempt to improve the performance, the structural change is made in conventional small fixed‐wing UAV through segmentation of each aileron control surface into multiples. Detailed system identification experiments are performed on each aileron pair in the wind tunnel to acquire linear dynamic models for the roll attitude of the UAV. These experiments have provided the transfer functions for the aileron control surfaces based on corresponding frequency response. Three distinctive model predictive controllers are designed and deployed in real‐time hardware to achieve the roll attitude control. The roll attitude control experiments are validated in wind tunnel under both normal and turbulent environments. The results show that multiple input and single output control system provides significant improvement in the roll attitude and disturbance rejection performance. The collective actuation of multiple control surfaces improves roll stability by to when compared to the single aileron pair based conventional control in the presence of turbulent flight conditions.

Representative linearised models for a wave energy converter using various levels of force excitation

In guiding the progression, development, and operation of wave energy converters (WECs) in a more efficient way, mathematical analysis and understanding of the dynamic process is essential. Mathematical WEC models, obtained either by numerical analysis or physical modelling, form the basis of most (model-based) energy maximising control strategies available in the literature, where experimental design and system identification methodology directly impact the resulting model. This study, using an experimental-based WEC model (which can be used for linear control design), investigates the dynamic behaviour of a WEC by analysing the dominant poles of the system, generated using fully nonlinear computational fluid dynamics (CFD)-based numerical wave tank (NWT) experiments. The aim is to effectively track the dominant dynamics of the WEC, using different force-input amplitude levels in the NWT setup, and perform a comparison with the classical linear boundary-element-methods (BEM) equivalent methodology. Thus, the presented case studies are shown to agree with previously proposed model assessment of linear WEC models, based on a free-decay NWT setup. In addition, the representative WEC models determined as part of this study can be used for WEC controller design, either singly, or using a form of model/controller gain scheduling.

Nonlinear multi-physical system identification of a chemical stirred tank

This paper presents a coupled electro-thermo-mechanical lumped parameter model for a chemical stirred tank, considering the device-related thermo-mechanical losses and process-related effects. This separation can help compute the key performance factors for competing processes during the scale-up. As the model has unknown thermo-mechanical parameters, two system identification experiment sets are conducted to determine the friction torque and heat transfer coefficient. A data acquisition system is developed in this study based on the Teensy 4.1 microcontroller to stream the logged data of the installed sensors on the serial port. An extended Kalman filter and a moving horizon estimation exploit the model and measurements to estimate the unknown model parameters. The results include the coupled electro-thermo-mechanical effects in estimating the heat transfer coefficient.

Optimization of Hydraulic Fine Blanking Press Control System Based on System Identification

Fine-blanking is a molding process based on the common blanking process, which obtains hydrostatic stress through blank holder reverse jacking, in order to increase material plasticity. It requires special equipment, namely a fine-blanking press, to complete the fine-blanking process. In this paper, the problem of the speed of the slide block fluctuation found in the actual use of a 12,000 kN hydraulic fine-blanking press after multi-stage pressure source optimization is studied. Firstly, the mathematical model of the motion of the slide block in the blanking stage of the hydraulic fine blanking press is established, and the accurate mathematical model in the blanking stage of the hydraulic fine-blanking press is obtained through the least square method system identification experiment. Aiming at the complex working situation of the fine-blanking press, a phased PID control strategy is creatively proposed. The optimal PID control parameters are obtained by a genetic algorithm, and established a fuzzy PID controller for the blanking stage to accurately control the movement speed of the slide block. The results show that the new control strategy is very effective in improving the movement accuracy of the slide block, effectively improving the machining accuracy and reducing the impact vibration of the hydraulic system.

Model-based impurity emission front control using deuterium fueling and nitrogen seeding in TCV

This paper presents the first result using nitrogen-seeded exhaust feedback control of the NII impurity emission front in TCV. The NII emission front position is consistently located below its commonly used CIII counterpart, indicating the NII emission front is representative of a colder plasma region. We demonstrate control of the NII impurity emission front position for two cases: (a) using nitrogen seeding as the sole actuator, and (b) using deuterium fueling as an actuator while injecting a small amount of nitrogen that remains a trace impurity. For sole nitrogen actuation, peak target current density is significantly reduced when the NII emission front approaches the x-point (≈50% for the NII front at the halfway point). When actuating with deuterium, peak target current density is less affected, which is explained by changes in fueling engendering a different scrape-off-layer plasma density. Perturbative (system identification) experiments show that nitrogen actuation induces a stronger, but slower, response of the NII emission front than deuterium actuation. Moving the NII emission front back to the target after pushing it towards the x-point has proven difficult, where both the NII front position and total radiated power do not reach pre-seeding conditions within the discharge time following termination of nitrogen injection. This result highlights the need to account for impurity retention for such seeded discharges in exhaust control strategies.

Dynamic Task Space Control Enables Soft Manipulators to Perform Real‐World Tasks

Dynamic motions are a key feature of robotic arms, enabling them to perform tasks quickly and efficiently. A majority of real‐world soft robots rely on a quasistatic control approach, without taking dynamic characteristics into consideration. As a result, robots with this restriction move slowly and are not able to adequately deal with forces, such as handling unexpected perturbations or manipulating objects. A dynamic approach to control and modeling would allow soft robots to move faster and handle external forces more efficiently. In previous studies, different aspects of modeling, dynamic control, and physical implementation have been examined separately, while their combination has yet to be thoroughly investigated. Herein, the accuracy of the dynamic model of the multisegment continuum robot is improved by adding new elements that include variable stiffness and actuation behavior. Then, this improved model is integrated with state‐of‐the‐art system identification and dynamic task space control and experiments are performed to validate this combination on a real‐world manipulator. As a means of encouraging future research on dynamic control for soft robotic manipulators, the source code is made available for modeling, control, and system identification, along with the recipes for fabricating the manipulator.

Experimental testing and system identification of the sliding bistable nonlinear energy sink implemented to a four-story structure model subjected to earthquake excitation

Bistable nonlinear energy sink system has been explored as an efficient vibration absorber in many areas. This paper aims to experimentally validate the seismic mitigation performance of sliding bistable nonlinear energy sink (SBNES) for multi-story building structures. An SBNES device was designed and placed on top of a four-story building structure model. Earthquake ground motions were applied through a shake table as the base excitation input into the structure model. By matching the time history envelope curves between the experiment and numerical simulation, the structural parameters of the primary structure, as well as the constitutive model of the SBNES, were experimentally determined. The comparisons between mitigated and unmitigated structural responses, including inter-story drift, acceleration, base-shear force and base-overturning moment of the primary structure, show that substantial reduction of structural seismic responses can be achieved by the SBNES device. The 1:1 transient internal resonance is verified as the dominant scheme for highly efficient targeted energy transfer. With respect to variation of peak ground acceleration, a relatively optimal interval distributed near the borderline of intra-well and inter-well regime is proposed for robust SBNES design. The test validates the potential of the SBNES strategy for both acceleration and displacement control of multi-story building structures.