Robustification in Repetitive and Iterative Learning Control

Repetitive Control (RC) and Iterative Learning Control (ILC) are control methods that specifically deal with periodic signals or systems with repetitive operations. They have wide applications in diverse areas from high-precision manufacturing to high-speed assembly, and nowadays these algorithms have even been applied to biomimetic walking robots, where tracking a periodic reference signal or rejecting periodic disturbances is desired. Compared to conventional feedback control designs (including the inverse dynamics method), RC and ILC improve the control performance over repetitions -- by learning from the previous input-output data, RC and ILC adaptively update the control input for the next run, aiming for zero tracking error in the hardware instead of in a model, as time goes to infinity. The stability robustness to model uncertainty however remains a fundamental topic as it determines the successful implementation of RC and ILC on any real-world system whose model dynamics cannot normally be determined precisely over all frequencies up to Nyquist. In the control field, there are various existing methods of robustification, such as Linear Matrix Inequality (LMI), mu-synthesis and H-infinity, but few of these methods offer intuitive information about how the stability robustness is achieved. In addition, many of these existing algorithms produce conservative stability boundaries, leaving room for further optimization and enhancement. In this study, several robustification approaches are developed, where better insight into the robustification design process and a tighter stability boundary are established. The first method presents an algorithm for RC compensator design that not only uses phase adjustments, but also adjusts the learning rate as a function of frequency to obtain improved robustification to model parameter uncertainty. The basic objective of this algorithm is to make the system learn at each frequency at the maximum rate consistent with the need for robustness at that frequency. The second method, on the other hand, explores the benefits of compromising on the zero tracking error requirement for frequencies that require extra robustness, making RC tolerate larger model errors. The third topic focuses on the development of robustification algorithms for Iterative Learning Control that is analogous to the above two RC robustification designs, extending frequency response concepts to finite time problems. The final approach to robustification treated in this dissertation is based on Matched Basic Function Repetitive Control (MBFRC), which individually addresses each frequency, eliminating the need for a robustifying zero phase low pass filter and the need for interpolation in data as required in conventional RC design. Furthermore, this algorithm only uses the frequency response knowledge at the frequencies addressed, and as long as the phase uncertainties at those frequencies are within +/- 90 deg the system is guaranteed stable for all sufficiently small projection gains

Symmetry and asymmetry from MEMS variable capacitor by nonlinear micro stoppers

Mechanical stoppers in MEMS capacitive systems can dramatically affect electrical performances and result in complicated mechanical dynamic responses. This paper introduces electromechanical coupling nonlinear dynamic responses in MEMS variable dual-capacitor with an effect of nonlinear and asymmetrical stoppers. We found that the capacitance in the electrical circuit system related to the first-order derivative of the output voltage on a load resistor, and the variable dual-capacitor was strongly affected by the coupling of up and down superposition instantaneous electrostatic force and limited space by the length of nonlinear stoppers. The numerical calculation results and the experimental results in our analysis based on our system had a good agreement, and the numerical simulation results presented rich nonlinear impacts dynamic responses through the imposed voltage and the height of stoppers in MEMS variable dual-capacitive device. The device in operation cannot reach the 0.6 time's initial gap due to small forcing amplitude (1.026 g). However, we observed that the movable plate and stoppers (across the 0.6 time's initial gap) had fierce impacts due to big forcing amplitude (4 g) on to the device. With asymmetric stopper each impact, we also concluded that the movable plate would experience attenuations of the displacement until the moment to the next impacts. Moreover, the height of stoppers can not only result in complicated dynamic motion of the movable plate, but also can modulate a voltage of the fixed plate with its asymmetry structure

Learning Event-Relevant Factors for Video Anomaly Detection

Most video anomaly detection methods discriminate events that deviate from normal patterns as anomalies. However, these methods are prone to interferences from event-irrelevant factors, such as background textures and object scale variations, incurring an increased false detection rate. In this paper, we propose to explicitly learn event-relevant factors to eliminate the interferences from event-irrelevant factors on anomaly predictions. To this end, we introduce a causal generative model to separate the event-relevant factors and event-irrelevant ones in videos, and learn the prototypes of event-relevant factors in a memory augmentation module. We design a causal objective function to optimize the causal generative model and develop a counterfactual learning strategy to guide anomaly predictions, which increases the influence of the event-relevant factors. The extensive experiments show the effectiveness of our method for video anomaly detection

Hydrodynamics of Butterfly-Mode Flapping Propulsion of Dolphin Pectoral Fins with Elliptical Trajectories

This article aims to numerically study the hydrodynamic performance of the bionic dolphin equipped with a pair of rigid pectoral fins. We use dynamic-grid technology and user-defined functions to simulate a novel butterfly-mode flapping propulsion of the fins. This pattern of propulsion is composed of three angular degrees of freedom including the pitch angle ϕp, the azimuth angle ϕa and the roll angle ϕr, which can be divided into four stages for analysis within a single cycle. The stroke of one single pectoral fin can be approximated as an ellipse trajectory, where the amplitudes of ϕa and ϕp, respectively, determine the major and minor axes of the ellipse. The fluid dynamics involved in the specific butterfly pattern is mathematically formulated, and numerical simulation is conducted to investigate the propulsion quantitatively. The results show that the dolphin with a higher water striking frequency f can acquire higher propulsion speed and efficiency. Furthermore, the shape of the ellipse trajectory under different conditions could also have different propulsion effects. The periodic generation and disappearance of vortex structures in the butterfly flapping mode show the evolution process of fluid flow around a pair of pectoral fins, which reveals the influence of motion parameters on fluid dynamics under different working conditions

Structural Design, Simulation and Experiment of Quadruped Robot

This paper carried out a series of designs, simulations and implementations by using the physical-like mechanism of a bionic quadruped robot dog as a vehicle. Through an investigation of the walking mechanisms of quadrupeds, a bionic structure is proposed that is capable of omnidirectional movements and smooth motions. Furthermore, the kinematic and inverse kinematic solutions based on the DH method are explored to lay the foundation for the gait algorithm. Afterward, a classical compound pendulum equation is applied as the foot-end trajectory and inverse kinematic solutions are combined to complete the gait planning. With appropriate foot–ground contact modeling, MATLAB and ADAMS are used to simulate the dynamic behavior and the diagonal trot gait of the quadruped robot. Finally, the physical prototype is constructed, designed and debugged, and its performance is measured through real-world experiments. Results show that the quadruped robot is able to balance itself during trot motion, for both its pitch and roll attitude. The goal of this work is to provide an affordable yet comprehensive platform for novice researchers in the field to study the dynamics, contact modeling, gait planning and attitude control of quadruped robots

Kinetic Walking Energy Harvester Design for a Wearable Bowden Cable-Actuated Exoskeleton Robot

Over the past few decades, wearable exoskeletons of various forms have been developed to assist human activities or for rehabilitation of movement disorders. However, sustainable exoskeletons with efficient energy harvesting devices still have not been fully explored. In this paper, we propose the design of a lightweight wearable Bowden-cable-actuated soft exoskeleton robot with energy harvesting capability. Unlike previous wearable exoskeletons, the presented exoskeleton uses an electromagnetic generator to both harvest biomechanical energy and to output mechanical torque by controlling an operation mode relay switch based on a human’s gait. Moreover, the energy-harvesting module also acts as a knee impact absorber for the human, where the effective damping level can be modulated in a controlled manner. The harvested energy is regulated and stored in super capacitors for powering wireless sensory devices when needed. The experimental results show an average of a 7.91% reduction in thigh muscle activity, with a maximum of 3.2 W of electric power being generated during movement downstairs. The proposed design offers important prospects for the realization of lightweight wearable exoskeletons with improved efficiency and long-term sustainability

Learning-Based Repetitive Control of a Bowden-Cable-Actuated Exoskeleton with Frictional Hysteresis

Bowden-cable-actuated soft exoskeleton robots are known for their light weight and flexibility of power transmission during rehabilitation training or movement assistance for humans. However, friction-induced nonlinearity of the Bowden transmission cable and gearbox backlash pose great challenges forprecise tracking control of the exoskeleton robot. In this paper, we proposed the design of a learning-based repetitive controller which could compensate for the non-linearcable friction and gearbox backlash in an iterative manner. Unlike most of the previous control schemes, the presented controller does not require apriori knowledge or intensive modeling of the friction and backlash inside the exoskeleton transmission system. Instead, it uses the iterative learning control (ILC)to adaptively update the reference trajectory so that the output hysteresis caused by friction and backlashis minimized. In particular, a digital phase-lead compensator was designed and integrated with the ILC to address the issue of backlash delay and improve the stability and tracking performance. Experimental results showed an average of seven iterations for the convergence of learning and a 91.1% reduction in the RMS tracking error (~1.37 deg) compared with the conventional PD control. The proposed controller design offers promising options for the realization of lightweight, wearable exoskeletons with high tracking accuracies

An Indole-3-Acetic Acid Carboxyl Methyltransferase Regulates Arabidopsis Leaf Development

Auxin is central to many aspects of plant development; accordingly, plants have evolved several mechanisms to regulate auxin levels, including de novo auxin biosynthesis, degradation, and conjugation to sugars and amino acids. Here, we report the characterization of an Arabidopsis thaliana mutant, IAA carboxyl methyltransferase1-dominant (iamt1-D), which displayed dramatic hyponastic leaf phenotypes caused by increased expression levels of the IAMT1 gene. IAMT1 encodes an indole-3-acetic acid (IAA) carboxyl methyltransferase that converts IAA to methyl-IAA ester (MeIAA) in vitro, suggesting that methylation of IAA plays an important role in regulating plant development and auxin homeostasis. Whereas both exogenous IAA and MeIAA inhibited primary root and hypocotyl elongation, MeIAA was much more potent than IAA in a hypocotyl elongation assay, indicating that IAA activities could be effectively regulated by methylation. IAMT1 was spatially and temporally regulated during the development of both rosette and cauline leaves. Changing expression patterns and/or levels of IAMT1 often led to dramatic leaf curvature phenotypes. In iamt1-D, the decreased expression levels of TCP genes, which are known to regulate leaf curvature, may partially account for the curly leaf phenotype. The identification of IAMT1 and the elucidation of its role in Arabidopsis leaf development have broad implications for auxin-regulated developmental process

Effect of Water Chemistry and Hydrodynamics on Nitrogen Transformation Activity and Microbial Community Functional Potential in Hyporheic Zone Sediment Columns

Hyporheic zones (HZ) are active biogeochemical regions where groundwater and surface water mix. N transformations in HZ sediments were investigated in columns with a focus on understanding how the dynamic changes in groundwater and surface water mixing affect microbial community and its biogeochemical function with respect to N transformations. The results indicated that denitrification, DNRA, and nitrification rates and products changed quickly in response to changes in water and sediment chemistry, fluid residence time, and groundwater–surface water exchange. These changes were accompanied by the zonation of denitrification functional genes along a 30 cm advective flow path after a total of 6 days’ elution of synthetic groundwater with fluid residence time >9.8 h. The shift of microbial functional potential toward denitrification was correlated with rapid NO₃^– reduction collectively affected by NO₃^– concentration and fluid residence time, and was resistant to short-term groundwater-surface water exchange on a daily basis. The results implied that variations in microbial functional potential and associated biogeochemical reactions in the HZ may occur at space scales where steep concentration gradients present along the flow path and the variations would respond to dynamic HZ water exchange over different time periods common to natural and managed riverine systems