593 research outputs found

    A Sequential Two-Step Algorithm for Fast Generation of Vehicle Racing Trajectories

    Full text link
    The problem of maneuvering a vehicle through a race course in minimum time requires computation of both longitudinal (brake and throttle) and lateral (steering wheel) control inputs. Unfortunately, solving the resulting nonlinear optimal control problem is typically computationally expensive and infeasible for real-time trajectory planning. This paper presents an iterative algorithm that divides the path generation task into two sequential subproblems that are significantly easier to solve. Given an initial path through the race track, the algorithm runs a forward-backward integration scheme to determine the minimum-time longitudinal speed profile, subject to tire friction constraints. With this fixed speed profile, the algorithm updates the vehicle's path by solving a convex optimization problem that minimizes the resulting path curvature while staying within track boundaries and obeying affine, time-varying vehicle dynamics constraints. This two-step process is repeated iteratively until the predicted lap time no longer improves. While providing no guarantees of convergence or a globally optimal solution, the approach performs very well when validated on the Thunderhill Raceway course in Willows, CA. The predicted lap time converges after four to five iterations, with each iteration over the full 4.5 km race course requiring only thirty seconds of computation time on a laptop computer. The resulting trajectory is experimentally driven at the race circuit with an autonomous Audi TTS test vehicle, and the resulting lap time and racing line is comparable to both a nonlinear gradient descent solution and a trajectory recorded from a professional racecar driver. The experimental results indicate that the proposed method is a viable option for online trajectory planning in the near future

    Contingency Model Predictive Control for Automated Vehicles

    Full text link
    We present Contingency Model Predictive Control (CMPC), a novel and implementable control framework which tracks a desired path while simultaneously maintaining a contingency plan -- an alternate trajectory to avert an identified potential emergency. In this way, CMPC anticipates events that might take place, instead of reacting when emergencies occur. We accomplish this by adding an additional prediction horizon in parallel to the classical receding MPC horizon. The contingency horizon is constrained to maintain a feasible avoidance solution; as such, CMPC is selectively robust to this emergency while tracking the desired path as closely as possible. After defining the framework mathematically, we demonstrate its effectiveness experimentally by comparing its performance to a state-of-the-art deterministic MPC. The controllers drive an automated research platform through a left-hand turn which may be covered by ice. Contingency MPC prepares for the potential loss of friction by purposefully and intuitively deviating from the prescribed path to approach the turn more conservatively; this deviation significantly mitigates the consequence of encountering ice.Comment: American Control Conference, July 2019; 6 page

    Atherosclerosis: cell biology and lipoproteins-focus on anti-inflammatory mechanisms as therapeutic options

    Get PDF

    Circulating Levels of Interleukin-1 Family Cytokines in Overweight Adolescents

    Get PDF
    Objectives. Obesity and related diseases are dramatically increasing problems, particularly in children and adolescents. We determined circulating levels of different interleukin (IL)-1 family members in normal weight and overweight adolescents. Methods. Seventy male, Caucasian adolescents (13–17 years) were recruited. Thirty-five had a body-mass index (BMI) above the 90th age-specific percentile. IL-1α, IL-1β, IL-1 receptor antagonist (IL-1ra), and IL-18 were determined using multiplex-technology. Results. IL-18 concentrations were higher in the overweight group compared to normal weight (161.6 ± 40.7 pg/ml versus 134.7 ± 43.4 pg/ml, P = .009). Concentrations of circulating IL-1β levels were below the detection threshold. IL-18 (R2:0.355, P < .01) and IL-1ra (R2:0.287, P < .05) correlated with BMI, whereas IL-1α did not. Conclusions. Accumulating data indicate the importance of the endocrine function of adipose tissue for the pathophysiological consequences of obesity-related co-morbidities. Since IL-18 is involved in the pathogenesis of different cardiovascular diseases, we conclude that IL-18 may represent a link between obesity and related co-morbidities in children and adolescents

    The bimodality of the East Siberian fast ice extent: mechanisms and changes

    Get PDF
    Using operational sea-ice maps, we provide first insight into the seasonal evolution of fast ice in the East Siberian Sea for the period between 1999 and 2021. The fast ice season tends to start later by 4.7 d per decade and to end earlier by 9.7 d per decade. As a result, there is a trend towards a shorter length of fast ice season by 2 weeks per decade. The analysis of air temperatures indicates that onset and end of the fast ice season are largely driven by thermodynamic processes. Two spatial modes (large, L-mode and small, S-mode) of East Siberian fast ice cover which have significant areal differences were distinguished. The occurrence of L- and S-modes was linked to the polarity of the Arctic Oscillation (AO) index. Negative AO phase leads to increased sea-ice convergence in the region, which in turn favours sea-ice grounding and promotes the development of large fast ice extent (L-mode). Lower deformation rates in the region during positive AO phase does not allow the formation of grounded features which results in small fast ice extent (S-mode). An analysis of sea-ice divergence confirms that L-mode seasons are characterised by higher on-shore convergence compared with S-mode seasons

    Development of a laser powder bed fusion process tailored for the additive manufacturing of high-quality components made of the commercial magnesium alloy WE43

    Get PDF
    Additive manufacturing (AM) has become increasingly important over the last decade and the quality of the products generated with AM technology has strongly improved. The most common metals that are processed by AM techniques are steel, titanium (Ti) or aluminum (Al) alloys. However, the proportion of magnesium (Mg) in AM is still negligible, possibly due to the poor processability of Mg in comparison to other metals. Mg parts are usually produced by various casting processes and the experiences in additive manufacturing of Mg are still limited. To address this issue, a parameter screening was conducted in the present study with experiments designed to find the most influential process parameters. In a second step, these parameters were optimized in order to fabricate parts with the highest relative density. This experiment led to processing parameters with which specimens with relative densities above 99.9% could be created. These highdensity specimens were then utilized in the fabrication of test pieces with several different geometries, in order to compare the material properties resulting from both the casting process and the powder bed fusion (PBF-LB) process. In this comparison, the compositions of the occurring phases and the alloys’ microstructures as well as the mechanical properties were investigated. Typically, the microstructure of metal parts, produced by PBF-LB, consisted of much finer grains compared to as-cast parts. Consequently, the strength of Mg parts generated by PBF-LB could be further increased. © 2021 by the authors. Licensee MDPI, Basel, Switzerland
    corecore