Preview Approach Research Articles

Exploring the experiences of undergraduate physics students taking a “Teaching Physics in School” module and the effects on their intentions to become a secondary physics teacher

This article describes an undergraduate physics module at a university in England that places year 3 student physicists in secondary school classrooms for a semester. This is done as a way of introducing them to the occupation of secondary physics teaching using a realistic job preview approach. The module helps the undergraduate students develop their communication and professional skills and supports the physics learning of pupils in the schools where they are placed. The perceptions of the participating students toward secondary school physics teaching are then investigated. Two themes emerged from this research: The difficulty of explaining physics concepts to children and the need to make school physics enjoyable.

Anti-Jerk Optimal Preview Control Strategy to Enhance Performance of Active and Semi-Active Suspension Systems

This study aims to demonstrate how to compute the damping coefficient of a continuously variable damper for semi-active preview control suspensions while considering the sprung-mass jerk and the controller’s performance advantage. Optimal control theory is used to derive and validate the proposed preview approach to future road disturbances. Despite reduced body acceleration, semi-active suspensions with preview control display an increase in body jerk, implying that ride comfort may not be improved in practice. The optimal preview jerk controller for a semi-active system, on the other hand, can improve ride comfort without degrading road holding by minimizing the performance index that comprises the RMS value of jerk in addition to the RMS values of other outputs. The anti-jerk preview control suspension simulations considering frequency characteristics reveal a difference between suspension systems that consider jerk and those that ignore jerk. The time-domain simulations suggest that the proposed preview control strategy effectively to reduce body jerk, which other controllers cannot.

Design and analysis of an integrated sliding mode control–two-point wheelbase preview strategy for a semi-active air suspension with stepper motor-driven gas-filled adjustable shock absorber

This article proposes an integrated sliding mode control–two-point wheelbase preview strategy for semi-active air suspension system with gas-filled adjustable shock absorber. First of all, a vehicle suspension model with rolling lobe air spring and gas-filled adjustable shock absorber is built, following with a road input model for the front wheel. By describing the detailed structure and working process of the gas-filled adjustable shock absorber, the regulating mechanism between the stepper motor and the designed gas-filled adjustable shock absorber is established. Subsequently, the sliding mode control algorithm is applied to generate the desired damping force with the real-time state of the vehicle. Moreover, to predetermine the road profile for the rear wheel, a two-point wheelbase preview approach is proposed and its superiority is also illustrated as compared with the conventional single-point wheelbase preview approach. To evaluate the performance of the proposed system, numerical analysis is conducted with other three comparative schemes, namely, passive suspension system, active suspension system with H infinity control, and sliding mode control–controlled semi-active air suspension system with adjustable shock absorber. Simulation results show that the integrated sliding mode control–two-point wheelbase preview strategy can be successfully utilized in the semi-active air suspension system with stepper motor-driven gas-filled adjustable shock absorber, and the vehicle performance with the proposed system can be greatly improved.

Braking Control in Railway Vehicles: A Distributed Preview Approach

The braking control problem for railway vehicles is considered. Communication flow from the front coaches to the rear ones is introduced, and a novel distributed braking control algorithm is proposed that, based on preview control theory, allows one to reduce the stopping distance. The effectiveness of the designed algorithm is corroborated by simulation comparisons to other standard approaches.

A greater understanding of social networks privacy requirements: The user perspective

Social Networks (SN) require an accurate understanding of the complex privacy requirements of users to demonstrate respect for user privacy requirements whilst also encouraging sharing. This research extends current understanding of SN user privacy requirements using the PREview approach, drawing on a thematic analysis of related scholarly articles and validating and extending themes by survey. The findings instantiate five primary privacy requirements including: Information Control, Information Collection and Storage, Information Access, Secondary Use, and Social Network Practice, and a further twenty five secondary requirements. This research has the potential to assist with the development of enhanced SN privacy controls.

A stochastic model predictive control approach for modelling human driver steering control

The simulation-based design and development of various vehicle active safety systems necessitate an enhanced understanding of the driver-vehicle-road system, and particular attention is paid to the improved modelling of the driver driving control characteristics. In this paper, a novel driver steering control model based on stochastic model predictive control (SMPC) is proposed to effectively incorporate the random variation characteristics of road friction. A multi-point driver preview approach is employed to represent the driver's perception of the desired path. An internal vehicle dynamic model with parameter uncertainty in the friction coefficient is formulated to represent the knowledge and adaptation of the driver to the variations in road conditions. A transport delay is applied to reflect the driver's physiological constraints. The SMPC method is then used to minimise a weighted cost function. Simulation and experimental validations are presented to demonstrate the effectiveness and practicability of the proposed modelling framework.

Switching-Based Stochastic Model Predictive Control Approach for Modeling Driver Steering Skill

Great advances in simulation-based vehicle system design and development of various driver assistance systems have enhanced the research on improved modeling of driver steering skills. However, little effort has been made on developing driver steering skill models while capturing the uncertainties or statistical properties of the vehicle-road system. In this paper, a stochastic model predictive control (SMPC) approach is proposed to model the driver steering skill, which effectively incorporates the random variations in the road friction and roughness, a multipoint preview approach, and a piecewise affine (PWA) model structure that are developed to mimic the driver's perception of the desired path and the nonlinear internal vehicle dynamics. The SMPC method is then used to generate a steering command by minimization of a cost function, including the lateral path error and ease of driver control. In the analyses, first, the experimental data of Hongqi HQ430 are used to validate the driver steering skill controller. Then, the parametric studies of control performance during a nonlinear steering maneuver are provided. Finally, further discussions about the driver's adaption and the indication on vehicle dynamics tuning are given. The proposed switching-based SMPC driver steering control framework offers a new approach for driver behavior modeling.

Two-degree-of-freedom ℓ 2-optimal tracking with preview

A simple SISO two-degree-of-freedom pole-placement design method is presented that provides ℓ 2-optimal tracking of a given reference signal. The closed-loop pole locations are first chosen by the system designer. The closed-loop zeros are then placed in an optimal fashion by a computationally inexpensive algorithm to achieve asymptotic tracking with an optimal transient response. The preview approach, which has become a common method for dealing with systems which have non-minimum phase behavior, can then optionally be used to further improve the transient behavior for both minimum phase and non-minimum phase systems. Unlike previous results based on the preview approach, the solution presented here takes into consideration the closed-loop pole dynamics, and is ℓ 2 optimal with respect to all other two-degree-of-freedom preview controllers with the same closed-loop poles. A simple solution to the H 2 model matching problem, where the design parameter Q is not rational, but polynomial, is the heart of the solution method.

Judging the worth of curriculum materials: A preview approach

Judging the worth of curriculum materials: A preview approach

A preview approach to force control of robot manipulators

Automated assembly operations that utilize robots tend to constrain the robot's motion due to the task geometry. This constrained motion is termed compliant motion. Complaint motion can be actively controlled using a method of force feedback based upon servo-loop compensation, or it can be passively controlled by mechanical devices integrated into the robot structure. The “preview approach” to force control presented in this paper is a scheme based on predictive calculation of the contact forces that develop at the interface between mating parts. The preview approach utilizes predicted, present and past information to execute motion control. Contact forces are calculated using a mathematical model of the assembly process and are then used to control the compliant motion through suitable compensation torques. The control algorithm used here is more efficient than the standard methods that rely on data from force sensors and use no preview.