Application of Optimal Control Theory to Inverse Simulation of Car Handling

The application of Optimal Control Theory to time-optimal inverse simulation of car handling was investigated. Time-optimal inverse simulation of car handling involves the calculation of driver actions required to perform specified manoeuvres, in as short a time as possible. Driver actions consist of time-histories of front wheel steer rate and longitudinal force. Optimal time-histories of these quantities were calculated using the Gradient method after formulating the problem as one of optimal control. Simulation results are presented for two different cars performing similar lane-changes. These results show significant differences in necessary driver actions for different cars and demonstrate the suitability of the approach taken.     

Modelling of high speed gas quenching

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Independent control of all-wheel-drive torque distribution

The sophistication of all-wheel-drive (AWD) technology is approaching the point where the drive torque to each wheel can be independently controlled. This potentially offers vehicle handling enhancements similar to those provided by dynamic stability control, but without the inevitable reduction in vehicle acceleration. Independent control of AWD torque distribution would therefore be especially beneficial under acceleration close to the limit of stability. A vehicle model of a typical sports sedan was developed in Simulink, with fully independent control of torque distribution. Box-Behnken experimental design was employed to determine which torque distribution parameters have the greatest impact on the vehicle course and acceleration. A proportional-integral control strategy was implemented, applying yaw rate feedback to vary the front-rear torque distribution and lateral acceleration feedback to adjust the left-right distribution. The resulting system shows a significant improvement over conventional driveline configurations under aggressive cornering acceleration on a high-μ surface. The performance approaches the theoretical limit for these conditions. In the medium term, such a system is only likely to be economically viable for premium vehicles. However, a future revolution of powertrain technology towards, for example, wheel-mounted motors, could realize these handling benefits far more widely.     

Hierarchical optimisation of the design parameters of a vehicle suspension system

This paper presents a design methodology for the mechanical systems entitled First Design. It is based on a hierarchical organisation of the design, taking into account the notion of robustness at an early phase of the project. The aim is to improve the quality of the system in order to make it robust, less sensitive to the variability of the external parameters and design parameters. We distinguish two main stages of the design cycle: one concerning functional parameters and another concerning physical parameters. The methodology is based on simplified models, on sensitivity analysis and on robust multi-objective optimisation. As an example, the methodology will be applied to the optimisation of vehicle suspension system design parameters. For each stage of the hierarchical design, adapted simplified models, sensitivity analyses and optimisation processes will be studied and applied to our vehicle suspension system.     

Computational Vibration Analysis of Vehicle Shimmy by a Power-Work Method

This paper presents the simulation of vehicle shimmy for a mid-size truck with focus on a computational analysis tool that measures the power and corresponding work in dissipating the excitation energy. After a review of shimmy theory the power and work equations and their response classification in vibrating systems are introduced. Next, model validation compares the full vehicle model to an actual test vehicle. Finally, two designs that suppress shimmy in the test vehicle are analyzed in the model by the power-work method, showing components that effectively dissipate the shimmy energy.     

Productivity,efficiency and technical change in the European railways: A non-parametric approach

The purpose of this paper is to analyse the evolution of productivity in the European railways in the period 1970–95. We use a non-parametric approach that enables changes in productivity to be broken down into variations in efficiency and technical change. The results indicate that the productivity growth is concentrated in the last period (1985–95), when the majority of the companies undertook processes of reforms. This increase in productivity is mainly due to technical progress. We also analyse the determinants of efficiency and, unlike other papers, the technical change, finding that the greater the degree of autonomy and financial independence, the higher the efficiency levels and technical change. This revised version was published online in June 2006 with corrections to the Cover Date.     

Optimal Linear Active Suspensions with Vibration Absorbers and Integral Output Feedback Control

The bandwidth of the body response to a road input in an active suspension may be considerably reduced if the axle motions are independently controlled and if, at the same time, the effects of static and dynamic loads are counteracted by integral action in the body force control system. The paper presents a further application of the Ferguson-Rekasius method, leading to optimal output control with incomplete state feedback. To achieve narrow bandwidth body response the support springs are replaced by hydraulic actuators, and vibration absorbers or active wheel dampers are employed for the control of the axle motions. Active wheel damping is the more effective and gives good results. Proportional-plus-integral control action is shown to reduce the transient body displacements due to external forces.     

一种基于模型的水声弱信号检测方法(英文)

Detection of weak underwater signals is an area of general interest in marine engineering. A weak signal detection scheme was developed; it combined nonlinear dynamical reconstruction techniques, radial basis function (RBF) neural networks and an extended Kalman filter (EKF). In this method chaos theory was used to model background noise. Noise was predicted by phase space reconstruction techniques and RBF neural networks in a synergistic manner. In the absence of a signal, prediction error stayed low and became relatively large when the input contained a signal. EKF was used to improve the convergence rate of the RBF neural network. Application of the scheme to different experimental data sets showed that the algorithm can detect signals hidden in strong noise even when the signal-to-noise ratio (SNR) is less than −40d B.     

活塞蓄能器式管路阻尼器的理论与试验研究(英文)

It can be beneficial to reduce vibrations in shipboard piping, so the authors designed a new kind of piping damper with a plunger-type accumulator. Special requirements for the piping damper included low impact displacement, low speed, as well as an appropriate locking speed. Inside the damper, a plunger-type accumulator was installed and on the outside of the piston rod, a tube with exposed corrugations was added. Between the piston and the cylinder, a clearance seal was added. Using mathematical modeling, the effects of the dynamic performance of the damper’s impact displacement on vibrations were observed. Changes to the clearance between the piston and the cylinder, the stiffness of the spring in the accumulator, the throttle valve size, and locking speed resistance of the damper were respectively simulated and studied. Based on the results of the simulation, dampers with optimal parameters were developed and tested with different accumulator spring stiffnesses and different throttles. The simulation and experimental results showed that parameters such as seal clearance between piston and cylinder, accumulator spring stiffness and throttle parameters have significant effects on the damper’s impact displacement, low speed resistance and locking speed.     

水下潜器改进S面控制及控制系统仿真(英文)

S surface controllers have been proven to provide effective motion control for an autonomous underwater vehicle (AUV). However, it is difficult to adjust their control parameters manually. Choosing the optimum parameters for the controller of a particular AUV is a significant challenge. To automate the process, a modified particle swarm optimization (MPSO) algorithm was proposed. It was based on immune theory, and used a nonlinear regression strategy for inertia weight to optimize AUV control parameters. A semi-physical simulation system for the AUV was developed as a platform to verify the proposed control method, and its structure was considered. The simulation results indicated that the semi-physical simulation platform was helpful, the optimization algorithm has good local and global searching abilities, and the method can be reliably used for an AUV.