Quantitative Feedback Theory Velocity Control of a Single-rod Pump-controlled Actuator Using a Novel Flow Compensation Circuit

This paper employs the quantitative feedback theory (QFT) to design a robust fixed-gain linear velocity controller for a newly developed single-rod pump-controlled actuator. The actuator operates in four quadrants, with a load force becoming resistive or assistive alternatively. The controller also satisfies tracking, stability and sensitivity specifications in the presence of a wide range of system parametric uncertainties. Its performance is examined on an instrumented John Deere JD-48 backhoe. The experimental results show that the controller can maintain the actuator velocity within an acceptable response envelope, despite variation in load mass as high as 163 kg and the hydraulic circuit switching between operating quadrants.

Response envelope analysis for quantitative evaluation of drug combinations

Motivation The concept of synergy between two agents, over a century old, is important to the fields of biology, chemistry, pharmacology and medicine. A key step in drug combination analysis is the selection of an additivity model to identify combination effects including synergy, additivity and antagonism. Existing methods for identifying and interpreting those combination effects have limitations. Results We present here a computational framework, termed response envelope analysis (REA), that makes use of 3D response surfaces formed by generalized Loewe Additivity and Bliss Independence models of interaction to evaluate drug combination effects. Because the two models imply two extreme limits of drug interaction (mutually exclusive and mutually non-exclusive), a response envelope defined by them provides a quantitatively stringent additivity model for identifying combination effects without knowing the inhibition mechanism. As a demonstration, we apply REA to representative published data from large screens of anticancer and antibiotic combinations. We show that REA is more accurate than existing methods and provides more consistent results in the context of cross-experiment evaluation. Availability and implementation The open-source software package associated with REA is available at: https://github.com/4dsoftware/rea. Supplementary information Supplementary data are available at Bioinformatics online.

Design of a low-bandwidth position controller based on system identification for an electro-hydrostatic actuator

In order to design a controller, mathematical model is usually derived first, either from physical laws or by employing a system identification technique. Physical laws may not fully define the system because of the existing uncertainties and/or difficulty to accurately model certain phenomenon. Therefore, the resulting controller may be too conservative. In this article, we design a low-bandwidth controller for an electro-hydrostatic actuator positioning system based on a system identification technique. The designed controller is also linear, fixed-gain and robust to system uncertainties. A set of offline parametric linear identifications are performed under different conditions, including various environmental stiffnesses, levels of actuator internal leakage, viscous dampings and load masses. The obtained family of identified models is then used to design a quantitative feedback theory controller that satisfies given tracking and stability specifications. In addition, the performance of the controller is examined against another quantitative feedback theory controller that is designed for the same system using physical laws. The performances of two controllers are examined on a test rig. Experimental results show that both quantitative feedback theory controllers are capable of maintaining actuator position within acceptable response envelope. However, the controller designed based on physical laws has higher bandwidth and therefore is more conservative.

Fault-Tolerant Actuating Pressure Controller Design for an Electrohydrostatic Actuator Experiencing a Leaky Piston Seal

Electrohydrostatic actuators (EHAs), as a class of pump-controlled hydraulic actuators, are known for energy efficiency and easy maintainability. Thus, they can be widely used in the situations where actuating pressure/force control of hydraulic actuators is essential. Examples are automotive active suspension, deep-drawing press, molding machine, and vibration isolation. However, a leaky piston seal in an EHA system can be especially problematic as it is not visually detectable, but causes internal leakage flowing across actuator chambers impairing the performance. This paper employs quantitative feedback theory (QFT) to design a robust fixed-gain linear actuating pressure controller that is tolerant to actuator internal leakage. Since QFT captures uncertainties by templates, representing frequency responses of the plant on Nichols chart, the first step, to design a QFT controller, is to establish plant templates. In doing so, a set of offline parametric system identifications are implemented, and the family of identified models, providing frequency responses, are used to design the QFT fault-tolerant controller. The controller also satisfies the prescribed design tolerances on tracking, stability and sensitivity (disturbance rejection at plant output) under different conditions, including various levels of actuator internal leakage, environmental stiffnesses, and load masses. The ability of the controller to maintain actuating pressure within the acceptable response envelope is demonstrated in experiments. The experimental results show that the system specifications are satisfied despite internal leakage up to 12 L/min.

Damping and vibration characteristics of basalt-aramid/epoxy hybrid composite laminates

Damping and vibration characteristics of basalt-aramid/epoxy hybrid composites with different basalt/aramid fiber mixing ratios were investigated. Unidirectional basalt and twill weave aramid fibers were used as reinforcement. Non-hybrid basalt/epoxy and aramid/epoxy composite laminates were also fabricated for comparison. Dynamic characteristics of the composite laminates were determined experimentally using dynamic modal analysis. Damping properties were calculated with the logarithmic decrement method using a vibration response envelope curve. Loss modulus, storage modulus and damping ratio of the structures were also considered. It was observed that the results of hybrid configurations showed a distribution between non-hybrid basalt/epoxy and aramid/epoxy composites. Furthermore, the employment of aramid fibers in composite laminates enhances the damping properties of laminates, but reduces the strength values.

Quantification and classification of neuronal responses in kernel-smoothed peristimulus time histograms

Peristimulus time histograms are a widespread form of visualizing neuronal responses. Kernel convolution methods transform these histograms into a smooth, continuous probability density function. This provides an improved estimate of a neuron's actual response envelope. We here develop a classifier, called the h-coefficient, to determine whether time-locked fluctuations in the firing rate of a neuron should be classified as a response or as random noise. Unlike previous approaches, the h-coefficient takes advantage of the more precise response envelope estimation provided by the kernel convolution method. The h-coefficient quantizes the smoothed response envelope and calculates the probability of a response of a given shape to occur by chance. We tested the efficacy of the h-coefficient in a large data set of Monte Carlo simulated smoothed peristimulus time histograms with varying response amplitudes, response durations, trial numbers, and baseline firing rates. Across all these conditions, the h-coefficient significantly outperformed more classical classifiers, with a mean false alarm rate of 0.004 and a mean hit rate of 0.494. We also tested the h-coefficient's performance in a set of neuronal responses recorded in humans. The algorithm behind the h-coefficient provides various opportunities for further adaptation and the flexibility to target specific parameters in a given data set. Our findings confirm that the h-coefficient can provide a conservative and powerful tool for the analysis of peristimulus time histograms with great potential for future development.