Clamp-Force Estimation for a Brake-by-Wire System: A Sensor-Fusion Approach

The elimination of a clamp-force sensor from brake-by-wire system designs is strongly demanded due to implementation difficulties and cost issues. In this paper, a new method is presented to estimate the clamp force based on other sensory information. This estimator fuses the outputs of two models to optimize the root-mean-square error (RMSE) of estimation. Experimental results show that the estimator can accurately track the true clamp force for high-speed cases as demanded by the antilock braking system controls. A training strategy has been used to ensure that the estimator can successfully adapt to parameter variations associated with wear. This paper is concluded with a discussion on the reliability of the developed clamp-force estimator.     

Finite Sample Bias of Robust Estimators in Segmentation of Closely Spaced Structures: A Comparative Study

This paper presents the design and implementation of a new comparative analytical framework for studying the usability of modern high breakdown robust estimators. The emphasis is on finding the intrinsic limits, in terms of size and relative spatial accuracy, of such techniques in solving the emerging challenges of the segmentation of fine structures. A minimum threshold for the distance between separable structures is shown to depend mainly on the scale estimation error. A scale invariant performance measure is introduced to quantify the finite sample bias of the scale estimate of a robust estimator and the measure is evaluated for some state-of-the-art high breakdown robust estimators using datasets containing at least two close but distinct structures with varying distances and inlier ratios. The results show that the new generation of density-based robust estimators (such as pbM-estimator and TSSE) have a poorer performance in problems with datasets containing only a small number of samples in each structure compared with ones based on direct processing of the residuals (such as MSSE). An important message of this paper is that an estimator that performs best in some circumstances, may not be competitive in others: particularly performance on data structures that are relatively large and/or well-separated vs closely spaced fine structures.     

Visual tracking of numerous targets via multi-Bernoulli filtering of image data

This paper presents a novel Bayesian method to track multiple targets in an image sequence without explicit detection. Our method is formulated based on finite set representation of the multi-target state and the recently developed multi-Bernoulli filter. Experimental results on sport player and cell tracking studies show that our method can automatically track numerous targets, and it outperforms the state-of-the-art in terms of false positive (false alarm) and false negative (missing) rates as detection error measures, and in terms of label switching rate and lost tracks ratio as tracking error measures.     

Real-Time Clamp Force Measurement in Electromechanical Brake Calipers

In brake-by-wire systems, central controllers require accurate information about the clamp force between the brake pad and the disc as a function of pad displacement, which is usually denoted as the characteristic curve of the caliper. Due to aging, temperature, and other environmental variations, caliper characteristic curves vary with time. Therefore, automatic caliper calibration in real-time is vital for high-performance braking action and vehicle safety. Due to memory and processing-power limitations, the calibration technique should be memory efficient and of low computational complexity. In a typical electromechanical-braking-system design, clamp force measurement variations with actuator displacement is hysteretic. This paper introduces a simple and memory-efficient real-time calibration technique in which a clamp-force model is fitted to the data samples around each hysteresis cycle. The model includes a Maxwell-slip model for the hysteresis caused by friction. Experimental results from the data recorded in various temperatures show that the proposed technique results in clamp force measurements with less than 0.7% error over the range of clamp-force variations. It is also shown that, by using these measurements, the characteristic curve can be accurately calibrated in real-time.     

Position sensing in brake-by-wire callipers using resolvers

Recent designs for brake-by-wire systems use "resolvers" to provide accurate and continuous measurements for the absolute position and speed of the rotor of the electric actuators in brake callipers (permanent magnet DC motors). Resolvers are absolute-angle transducers that are integrated with estimator modules called "angle tracking observer" and together they provide position and speed measurements. Current designs for angle-tracking observers are unstable in applications with high acceleration and/or speed. In this paper, we introduce a new angle-tracking observer in which a closed-loop linear time-invariant (LTI) observer is integrated with a quadrature encoder. Finite-gain stability of the proposed design and its robustness to three different kinds of parameter variations are proven based on theorems of input-output stability in nonlinear control theory. In our experiments, we examined the performance of our observer and two other methods (a well-known LTI observer and an extended Kalman filter) to estimate the position and speed of a brake-by-wire actuator. The results show that because of the very high speed and acceleration of the actuator in this application, the LTI observer and Kalman filter cannot track the rotor position and diverge. In contrast, with a properly designed open-loop transfer function and selecting a suitable switching threshold, our proposed angle-tracking observer is stable and highly accurate in a brake-by-wire application.