On the passivity of interaction control with series elastic actuation

Regulating the mechanical interaction between robot and environment is a fundamentally important problem in robotics. Many applications such as manipulation and assembly tasks necessitate interaction control. Applications in which the robots are expected to collaborate and share the workspace with humans also require interaction control. Therefore, interaction controllers are quintessential to physical human-robot interaction (pHRI) applications. Passivity paradigm provides powerful design tools to ensure the safety of interaction. It relies on the idea that passive systems do not generate energy that can potentially destabilize the system. Thus, coupled stability is guaranteed if the controller and the environment are passive. Fortunately, passive environments constitute an extensive and useful set, including all combinations of linear or nonlinear masses, springs, and dampers. Moreover, a human operator may also be treated as a passive network element. Passivity paradigm is appealing for pHRI applications as it ensures stability robustness and provides ease-of-control design. However, passivity is a conservative framework which imposes stringent limits on control gains that deteriorate the performance. Therefore, it is of paramount importance to obtain the most relaxed passivity bounds for the control design problem. Series Elastic Actuation (SEA) has become prevalent in pHRI applications as it provides considerable advantages over traditional sti actuators in terms of stability robustness and delity of force control, thanks to deliberately introduced compliance between the actuator and the load. Several impedance control architectures have been proposed for SEA. Among the alternatives, the cascaded controller with an inner-most velocity loop, an intermediate torque loop and an outer-most impedance loop is particularly favoured for its simplicity, robustness, and performance. In this thesis, we derive the necessary and su cient conditions to ensure the passivity of the cascade-controller architecture for rendering two classical linear impedance models of null impedance and pure spring. Based on the newly established passivity conditions, we provide non-conservative design guidelines to haptically display free-space and virtual spring while ensuring coupled stability, thus the safety of interaction. We demonstrate the validity of these conditions through simulation studies as well as physical experiments. We demonstrate the importance of including physical damping in the actuator model during derivation of passivity conditions, when integral controllers are utilized. We note the unintuitive adversary e ect of actuator damping on system passivity. More precisely, we establish that the damping term imposes an extra bound on controller gains to preserve passivity. We further study an extension to the cascaded SEA control architecture and discover that series elastic damping actuation (SEDA) can passively render impedances that are out of the range of SEA. In particular, we demonstrate that SEDA can passively render Voigt model and impedances higher than the physical spring-damper pair in SEDA. The mathematical analyses of SEDA are veri ed through simulations

Necessary and sufficient conditions for the passivity of impedance rendering with velocity-sourced series elastic actuation

Series elastic actuation (SEA) has become prevalent in applications involving physical human-robot interaction, as it provides considerable advantages over traditional stiff actuators in terms of stability robustness and force control fidelity. Several impedance control architectures have been proposed for SEA. Among these alternatives, the cascaded controller with an innermost velocity loop, an intermediate torque loop, and an outermost impedance loop is particularly favored for its simplicity, robustness, and performance. In this article, we derive the necessary and sufficient conditions for passively rendering null impedance and virtual springs with this cascade-controller architecture. Based on the newly established conditions, we provide nonconservative passivity design guidelines to haptically display these two impedance models, which serve as the basic building blocks of various virtual environments, while ensuring the safety of interaction. We also demonstrate the importance of including physical damping in the actuator model for deriving the passivity conditions, when integrators are utilized. In particular, we prove the unintuitive adversary effect of physical damping on the passivity of the system by noting that the damping term reduces the system Z-width, as well as introducing an extra passivity constraint. Finally, we experimentally validate our theoretical results using an SEA brake pedal

Fast one- and two-pick fixed-priority selection and muxing circuits

Due to copyright restrictions, the access to the full text of this article is only available via subscription.Priority encoders and arbiters usually drive multiplexers (muxes). Latency optimization of priority encoders and multiplexer trees has usually been handled separately in the literature. However, in some applications with circular data dependencies, the combined latency of the arbiter and muxing needs to be optimized. Moreover, there is an ever growing need for throughput. This requires switches that pick and multiplex more than one request per cycle. In this paper, we propose a family of circuit topologies where priority encoding picks one or two requests and takes place in parallel with muxing. We first present a scalable logic circuit for the 1-pick fixed-priority muxing problem and then extend it to the 2-pick problem. We compare the proposed architecture to its counterpart that does only priority encoding using Synopsis Design Compiler with ARM-Artisan TSMC 180 nm worst-case standard library. The results show that most of the priority encoding latency is hidden in the proposed circuit topology

Prediction of thermal growth in a high-speed spindle by considering thermo-mechanical behavior

Continuous rotation of spindle bearings and motor cause thermally induced structural deformations and thermal growth, which is one of the main reasons for machining errors. A positive feedback loop between bearing preload and heat generation causes preload variations in spindle bearings. These preload variations demonstrate a nonlinear transient behavior until the gradual expansion of outer bearing rings after which the thermally induced preload variation behaves steadily. In this study, a Finite Element (FE) framework is presented for predicting steady preload variation on spindle bearings. The method involves a thermal loading model and a transient contact analysis. In the contact analysis phase bearing contact deformations (penetration and sliding) and pressure are predicted by considering contact algorithms in an FE software. A transient spindle simulation in FE is employed to predict the bearing temperature and thermal spindle growth by using the proposed method. The performance of the method is demonstrated on a spindle prototype through bearing temperature and thermal deformation measurements. Results show that the proposed method can be a useful tool for spindle design and improvements due to its promising results and speed without the need for tests

Quickest detection of bias injection attacks on the glucose sensor in the artificial pancreas under meal disturbances

Modern glucose sensors deployed in closed-loop insulin delivery systems, so-called artificial pancreas use wireless communication channels. While this allows a flexible system design, it also introduces vulnerability to cyberattacks. Timely detection and mitigation of attacks are imperative for device safety. However, large unknown meal disturbances are a crucial challenge in determining whether the sensor has been compromised or the sensor glucose trajectories are normal. We address this issue from a control-theoretic security perspective. In particular, a time-varying Kalman filter is employed to handle the sporadic meal intakes. The filter prediction error is then statistically evaluated to detect anomalies if present. We compare two state-of-the-art online anomaly detection algorithms, namely the χ2 and CUSUM tests. We establish a robust optimal detection rule for unknown bias injections. Even if the optimality holds only for the restrictive case of constant bias injections, we show that the proposed model-based anomaly detection scheme is also effective for generic non-stealthy sensor deception attacks through numerical simulations.ISSN:0959-1524ISSN:1873-277

Design and Analysis of a 5-Axis Gantry CNC Machine Tool

In this study, design and analysis of a gantry-type 5-axis CNC machine tool is presented with experimental results on a manufactured prototype. Critical points in the design of a large-scaled and heavy-duty machine tool is discussed. Moreover, FE analysis results is also presented with detailed discussion. The measurement results on structural dynamics is shown together with the FE results. Furthermore, the final performance of the machine tool is demonstrated thorough position and velocity measurements of the axes

Design and Analysis of a 5-Axis Gantry CNC Machine Tool

In this study, design and analysis of a gantry-type 5-axis CNC machine tool is presented with experimental results on a manufactured prototype. Critical points in the design of a large-scaled and heavy-duty machine tool is discussed. Moreover, FE analysis results is also presented with detailed discussion. The measurement results on structural dynamics is shown together with the FE results. Furthermore, the final performance of the machine tool is demonstrated thorough position and velocity measurements of the axes

Quickest detection of bias injection attacks on the glucose sensor in the artificial pancreas under meal disturbances

Modern glucose sensors deployed in closed -loop insulin delivery systems, so-called artificial pancreas use wireless communication channels. While this allows a flexible system design, it also introduces vulnerability to cyberattacks. Timely detection and mitigation of attacks are imperative for device safety. However, large unknown meal disturbances are a crucial challenge in determining whether the sensor has been compromised or the sensor glucose trajectories are normal. We address this issue from a control -theoretic security perspective. In particular, a time -varying Kalman filter is employed to handle the sporadic meal intakes. The filter prediction error is then statistically evaluated to detect anomalies if present. We compare two state-of-the-art online anomaly detection algorithms, namely the ￜￜￜￜￜￜ2 and CUSUM tests. We establish a robust optimal detection rule for unknown bias injections. Even if the optimality holds only for the restrictive case of constant bias injections, we show that the proposed model -based anomaly detection scheme is also effective for generic non -stealthy sensor deception attacks through numerical simulations