Self-Feedback Motion Control for Cable-Driven Parallel Manipulators

This article proposes a closed-loop control scheme based on joint-angle feedback for cable-driven parallel manipulators (CDPMs), which is able to overcome various difficulties resulting from the flexible nature of the driven cables to achieve higher control accuracy. By introducing a unique structure design that accommodates built-in encoders in passive joints, the seven degrees of freedom (7-DOF) CDPM can obtain joint angle values without external sensing devices, and it is used for feedback control together with a proper closed-loop control algorithm. The control algorithm has been derived from the time differential of the kinematic formulation, which relates the joint angular velocities to the time derivative of cable lengths. In addition, the Lyapunov stability theory and Monte Carlo method have been used to mathematically verify the self-feedback control law that has tolerance for parameter errors. With the aid of co-simulation technique, the self-feedback closed-loop control is applied on a 7-DOF CDPM and it shows higher motion accuracy than the one with an open-loop control. The trajectory tracking experiment on the motion control of the 7-DOF CDPM demonstrated a good performance of the self-feedback control method.

Parallel Robot

Parallel robot (PR) is a mechanical system that utilized multiple computer-controlled limbs to support one common platform or end effector. Comparing to a serial robot, a PR generally has higher precision and dynamic performance and, therefore, can be applied to many applications. The PR research has attracted a lot of attention in the last three decades, but there are still many challenging issues to be solved before achieving PRs’ full potential. This chapter introduces the state-of-the-art PRs in the aspects of synthesis, design, analysis, and control. The future directions will also be discussed at the end.

Shortening design time through multiplatform simulations with a portable OpenCL golden-model: the LDPC decoder case

Hardware designers and engineers typically need to explore a multi-parametric design space in order to find the best configuration for their designs using simulations that can take weeks to months to complete. For example, designers of special purpose chips need to explore parameters such as the optimal bitwidth and data representation. This is the case for the development of complex algorithms such as Low-Density Parity-Check (LDPC) decoders used in modern communication systems. Currently, high-performance computing offers a wide set of acceleration options, that range from multicore CPUs to graphics processing units (GPUs) and FPGAs. Depending on the simulation requirements, the ideal architecture to use can vary. In this paper we propose a new design flow based on OpenCL, a unified multiplatform programming model, which accelerates LDPC decoding simulations, thereby significantly reducing architectural exploration and design time. OpenCL-based parallel kernels are used without modifications or code tuning on multicore CPUs, GPUs and FPGAs. We use SOpenCL (Silicon to OpenCL), a tool that automatically converts OpenCL kernels to RTL for mapping the simulations into FPGAs. To the best of our knowledge, this is the first time that a single, unmodified OpenCL code is used to target those three different platforms. We show that, depending on the design parameters to be explored in the simulation, on the dimension and phase of the design, the GPU or the FPGA may suit different purposes more conveniently, providing different acceleration factors. For example, although simulations can typically execute more than 3x faster on FPGAs than on GPUs, the overhead of circuit synthesis often outweighs the benefits of FPGA-accelerated execution.

An efficacy and mechanism evaluation study of Levosimendan for the Prevention of Acute oRgan Dysfunction in Sepsis (LeoPARDS): Protocol for a randomized controlled trial

Background

Organ dysfunction consequent to infection (‘severe sepsis’) is the leading cause of admission to an intensive care unit (ICU). In both animal models and early clinical studies the calcium channel sensitizer levosimendan has been demonstrated to have potentially beneficial effects on organ function. The aims of the Levosimendan for the Prevention of Acute oRgan Dysfunction in Sepsis (LeoPARDS) trial are to identify whether a 24-hour infusion of levosimendan will improve organ dysfunction in adults who have septic shock and to establish the safety profile of levosimendan in this group of patients.

This is a multicenter, randomized, double-blind, parallel group, placebo-controlled trial. Adults fulfilling the criteria for systemic inflammatory response syndrome due to infection, and requiring vasopressor therapy, will be eligible for inclusion in the trial. Within 24 hours of meeting these inclusion criteria, patients will be randomized in a 1:1 ratio stratified by the ICU to receive either levosimendan (0.05 to 0.2 μg.kg^-1.min^-1 or placebo for 24 hours in addition to standard care. The primary outcome measure is the mean Sequential Organ Failure Assessment (SOFA) score while in the ICU. Secondary outcomes include: central venous oxygen saturations and cardiac output; incidence and severity of renal failure using the Acute Kidney Injury Network criteria; duration of renal replacement therapy; serum bilirubin; time to liberation from mechanical ventilation; 28-day, hospital, 3 and 6 month survival; ICU and hospital length-of-stay; and days free from catecholamine therapy. Blood and urine samples will be collected on the day of inclusion, at 24 hours, and on days 4 and 6 post-inclusion for investigation of the mechanisms by which levosimendan might improve organ function. Eighty patients will have additional blood samples taken to measure levels of levosimendan and its active metabolites OR-1896 and OR-1855. A total of 516 patients will be recruited from approximately 25 ICUs in the United Kingdom.

This trial will test the efficacy of levosimendan to reduce acute organ dysfunction in adult patients who have septic shock and evaluate its biological mechanisms of action.

Barriers to Goals of Care Discussions With Seriously Ill Hospitalized Patients and Their Families: A Multicenter Survey of Clinicians

Importance: Seriously ill hospitalized patients have identified communication and decision making about goals of care as high priorities for quality improvement in end-of-life care. Interventions to improve care are more likely to succeed if tailored to existing barriers.

Objective: To determine, from the perspective of hospital-based clinicians, (1) barriers impeding communication and decision making about goals of care with seriously ill hospitalized patients and their families and (2) their own willingness and the acceptability for other clinicians to engage in this process.

Design, Setting, and Participants: Multicenter survey of medical teaching units of nurses, internal medicine residents, and staff physicians from participating units at 13 university-based hospitals from 5 Canadian provinces.

Main Outcomes and Measures: Importance of 21 barriers to goals of care discussions rated on a 7-point scale (1 = extremely unimportant; 7 = extremely important).

Results: Between September 2012 and March 2013, questionnaires were returned by 1256 of 1617 eligible clinicians, for an overall response rate of 77.7% (512 of 646 nurses [79.3%], 484 of 634 residents [76.3%], 260 of 337 staff physicians [77.2%]). The following family member-related and patient-related factors were consistently identified by all 3 clinician groups as the most important barriers to goals of care discussions: family members' or patients' difficulty accepting a poor prognosis (mean [SD] score, 5.8 [1.2] and 5.6 [1.3], respectively), family members' or patients' difficulty understanding the limitations and complications of life-sustaining treatments (5.8 [1.2] for both groups), disagreement among family members about goals of care (5.8 [1.2]), and patients' incapacity to make goals of care decisions (5.6 [1.2]). Clinicians perceived their own skills and system factors as less important barriers. Participants viewed it as acceptable for all clinician groups to engage in goals of care discussions-including a role for advance practice nurses, nurses, and social workers to initiate goals of care discussions and be a decision coach.

Conclusions and Relevance: Hospital-based clinicians perceive family member-related and patient-related factors as the most important barriers to goals of care discussions. All health care professionals were viewed as playing important roles in addressing goals of care. These findings can inform the design of future interventions to improve communication and decision making about goals of care.

Enhancing design space exploration by extending CPU/GPU specifications onto FPGAs

The design cycle for complex special-purpose computing systems is extremely costly and time-consuming. It involves a multiparametric design space exploration for optimization, followed by design verification. Designers of special purpose VLSI implementations often need to explore parameters, such as optimal bitwidth and data representation, through time-consuming Monte Carlo simulations. A prominent example of this simulation-based exploration process is the design of decoders for error correcting systems, such as the Low-Density Parity-Check (LDPC) codes adopted by modern communication standards, which involves thousands of Monte Carlo runs for each design point. Currently, high-performance computing offers a wide set of acceleration options that range from multicore CPUs to Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs). The exploitation of diverse target architectures is typically associated with developing multiple code versions, often using distinct programming paradigms. In this context, we evaluate the concept of retargeting a single OpenCL program to multiple platforms, thereby significantly reducing design time. A single OpenCL-based parallel kernel is used without modifications or code tuning on multicore CPUs, GPUs, and FPGAs. We use SOpenCL (Silicon to OpenCL), a tool that automatically converts OpenCL kernels to RTL in order to introduce FPGAs as a potential platform to efficiently execute simulations coded in OpenCL. We use LDPC decoding simulations as a case study. Experimental results were obtained by testing a variety of regular and irregular LDPC codes that range from short/medium (e.g., 8,000 bit) to long length (e.g., 64,800 bit) DVB-S2 codes. We observe that, depending on the design parameters to be simulated, on the dimension and phase of the design, the GPU or FPGA may suit different purposes more conveniently, thus providing different acceleration factors over conventional multicore CPUs.

Towards generalized Doherty power amplifier design for multiband operation

This paper presents a new variant of broadband Doherty power amplifier that employs a novel output combiner. A new parameter ∝ is introduced to permit a generalized analysis of the recently reported Parallel Doherty power amplifier (PDPA),and hence offer design flexibility. The circuit prototype of the new DPA fabricated using GaN devices exhibits maximum drain efficiency of 85% at 43-dBm peak power and 63% at 6-dB backoff power (BOP). Measured drain efficiency of >60% at peak power across 500-MHz frequency range and >50% at 6-dB BOP across 480-MHz frequency range were achieved, confirming the  theoretical wideband characteristics of the new DPA.

Elastodynamic Modeling and Analysis for an Exechon Parallel Kinematic Machine

As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.

Photon nanojet lens: Design, fabrication and characterization

In this paper, a novel nanolens with super resolution, based on the photon nanojet effect through dielectric nanostructures in visible wavelengths, is proposed. The nanolens is made from plastic SU-8, consisting of parallel semi-cylinders in an array. This paper focuses on the lens designed by numerical simulation with the finite-difference time domain method and nanofabrication of the lens by grayscale electron beam lithography combined with a casting/bonding/lift-off transfer process. Monte Carlo simulation for injected charge distribution and development modeling was applied to define the resultant 3D profile in PMMA as the template for the lens shape. After the casting/bonding/lift-off process, the fabricated nanolens in SU-8 has the desired lens shape, very close to that of PMMA, indicating that the pattern transfer process developed in this work can be reliably applied not only for the fabrication of the lens but also for other 3D nanopatterns in general. The light distribution through the lens near its surface was initially characterized by a scanning near-field optical microscope, showing a well defined focusing image of designed grating lines. Such focusing function supports the great prospects of developing a novel nanolithography based on the photon nanojet effect.

Series-L/parallel-tuned Class-E power amplifier analysis

An analysis of the operation of a new series-L/parallel-tuned Class-E amplifier and its equivalence to the classic shunt-C/series-tuned Class-E amplifier are presented. The first reported closed form design equations for the series-L/parallel-tuned topology operating under ideal switching conditions are given, including the switch current and voltage in steady state, the circuit component values, the peak values of switch current and voltage and the power-output capability. Theoretical analysis is confirmed by numerical simulation for a 500 mW (27 dBm), 10% bandwidth, 5 V series-L/parallel-tuned, then, shunt-C/series-tuned Class-E power amplifier, operating at 2.5 GHz. Excellent agreement between theory and simulation results is achieved.

An Environment for Rapid Derivatives Design and Experimentation

In the highly competitive world of modern finance, new derivatives are continually required to take advantage of changes in financial markets, and to hedge businesses against new risks. The research described in this paper aims to accelerate the development and pricing of new derivatives in two different ways. Firstly, new derivatives can be specified mathematically within a general framework, enabling new mathematical formulae to be specified rather than just new parameter settings. This Generic Pricing Engine (GPE) is expressively powerful enough to specify a wide range of stand¬ard pricing engines. Secondly, the associated price simulation using the Monte Carlo method is accelerated using GPU or multicore hardware. The parallel implementation (in OpenCL) is automatically derived from the mathematical description of the derivative. As a test, for a Basket Option Pricing Engine (BOPE) generated using the GPE, on the largest problem size, an NVidia GPU runs the generated pricing engine at 45 times the speed of a sequential, specific hand-coded implementation of the same BOPE. Thus a user can more rapidly devise, simulate and experiment with new derivatives without actual programming.