Control Design for Automated Vehicle Emergency Safe Stop System Based on Differential Dynamic Programming

2020 ◽  
Author(s):  
Lisheng Yang ◽  
Tomonari Furukawa ◽  
Lei Zuo ◽  
Zachary Doerzaph
Keyword(s):  
Dynamic Programming ◽  
Real Time ◽  
Control Algorithm ◽  
Computation Time ◽  
Grid Cell ◽  
System Control ◽  
Real Time Control ◽  
Differential Dynamic Programming ◽  
Time Control ◽  
Emergency Stop

Abstract This paper presents the control algorithm and system design for a newly proposed automated emergency stop system, which aims to navigate the vehicle out of its travel lane to a safe road-side location when an emergency (e.g. driver fails to take control during fallback of the Dynamic Driving Task) occurs. To address the unique requirements of such a system, control techniques based on differential dynamic programming are developed. Optimal control sequence computation is broken down into step-by-step quadratic optimization and solved iteratively. Control constraints are addressed efficiently by a tailored Projected-Newton algorithm. The iterative control algorithm is then integrated into a real-time control system which considers both computation delay and modeling errors. The system employs a novel grid-based storage structure for recording all acceptable control commands computed within the iteration and uses a high frequency estimator for self-localization. During operation, the real-time control thread will extract commands from the grid cell corresponding to current states. Simulation results show strong potential of the proposed system for addressing the engineering challenges of the automated emergency stop function. The robustness of the system in presence of computation time delay and modelling errors is also demonstrated.

Optimal control of a novel uninterrupted multi-speed transmission for hybrid electric mining trucks

2019 ◽  
Vol 233 (12) ◽  
pp. 3235-3245 ◽  
Author(s):  
Weiwei Yang ◽  
Jiejunyi Liang ◽  
Jue Yang ◽  
Nong Zhang
Keyword(s):  
Dynamic Programming ◽  
Real Time ◽  
Control Strategy ◽  
Dynamic Models ◽  
Fuel Efficiency ◽  
Real Time Control ◽  
Traction Motor ◽  
Time Control ◽  
Power Split ◽  
Shift Strategy

Considering the energy consumption and specific performance requirements of mining trucks, a novel uninterrupted multi-speed transmission is proposed in this paper, which is composed of a power-split device, and a three-speed lay-shaft transmission with a traction motor. The power-split device is adapted to enhance the efficiency of the engine by adjusting the gear ratio continuously. The three-speed lay-shaft transmission is designed based on the efficiency map of traction motor to guarantee the drivability. The combination of the power-split device and three-speed lay-shaft transmission can realize uninterrupted gear shifting with the proposed shift strategy, which benefits from the proposed adjunct function by adequately compensating the torque hole. The detailed dynamic models of the system are built to verify the effectiveness of the proposed shift strategy. To evaluate the maximum fuel efficiency that the proposed uninterrupted multi-speed transmission could achieve, dynamic programming is implemented as the baseline. Due to the “dimension curse” of dynamic programming, a real-time control strategy is designed, which can significantly improve the computing efficiency. The simulation results demonstrate that the proposed uninterrupted multi-speed transmission with dynamic programming and real-time control strategy can improve fuel efficiency by 11.63% and 8.51% compared with conventional automated manual transmission system, respectively.

An application of real-time control systems to robotics

Robotica ◽  
2001 ◽  
Vol 19 (3) ◽  
pp. 323-329 ◽  
Author(s):  
Carmen Monroy ◽  
Ricardo Campa ◽  
Rafael Kelly
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Control Algorithm ◽  
Computing Environment ◽  
Real Time Control ◽  
Time Control ◽  
On Line ◽  
Robot Performance ◽  
Single Processor ◽  
Selection Of

This paper illustrates basic concepts of real-time control systems through the application of a real-time single-processor computing environment for the control of a robotic arm. The paper describes elements for the selection of the real-time architecture, the control algorithm and the graphical user interface. The system provides an opportunity for users to verify the robot performance by changing on-line the controller parameters and the shape of the desired motion.

scholarly journals Optimisation of a fuzzy logic-based local real-time control system for mitigation of sewer flooding using genetic algorithms

2019 ◽  
Vol 22 (2) ◽  
pp. 281-295 ◽  
Author(s):  
S. R. Mounce ◽  
W. Shepherd ◽  
S. Ostojin ◽  
M. Abdel-Aal ◽  
A. N. A. Schellart ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Control Algorithm ◽  
Expert Knowledge ◽  
Economic Losses ◽  
Rainfall Time Series ◽  
Real Time Control ◽  
Spare Capacity ◽  
Time Control ◽  
Drainage Networks

Abstract Urban flooding damages properties, causes economic losses and can seriously threaten public health. An innovative, fuzzy logic (FL)-based, local autonomous real-time control (RTC) approach for mitigating this hazard utilising the existing spare capacity in urban drainage networks has been developed. The default parameters for the control algorithm, which uses water level-based data, were derived based on domain expert knowledge and optimised by linking the control algorithm programmatically to a hydrodynamic sewer network model. This paper describes a novel genetic algorithm (GA) optimisation of the FL membership functions (MFs) for the developed control algorithm. In order to provide the GA with strong training and test scenarios, the compiled rainfall time series based on recorded rainfall and incorporating multiple events were used in the optimisation. Both decimal and integer GA optimisations were carried out. The integer optimisation was shown to perform better on unseen events than the decimal version with considerably reduced computational run time. The optimised FL MFs result in an average 25% decrease in the flood volume compared to those selected by experts for unseen rainfall events. This distributed, autonomous control using GA optimisation offers significant benefits over traditional RTC approaches for flood risk management.

Dimensioning battery energy storage systems for peak shaving based on a real-time control algorithm

2020 ◽  
Vol 280 ◽  
pp. 115993
Author(s):  
Christopher Lange ◽  
Alexandra Rueß ◽  
Andreas Nuß ◽  
Richard Öchsner ◽  
Martin März
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Control Algorithm ◽  
Storage Systems ◽  
Real Time Control ◽  
Peak Shaving ◽  
Battery Energy Storage ◽  
Time Control ◽  
Battery Energy Storage Systems ◽  
Battery Energy
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