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Development of a controller to perform an automatic lateral emergency collision avoidance manoeuvre for a passenger car
Abstract
An automatic controller is being developed to cause a passenger car to perform a lateral emergency collision avoidance manoeuvre: a single lane change at high speed, while operating at the vehicle's physical limits. The car is stabilised about a predetermined velocity profile by a feedforward steering action based on the Ackermann steering angle, combined with a feedback control loop which uses the anti-lock braking system to apply differential torques to each of the wheels. The forces to be applied to each wheel are calculated using the pseudo-inverse of a velocity-based linearisation of a system model. This inverse controller acts upon a signal containing the lateral and yaw veloc-ity error, fed back through a scheduled gain matrix; the matrix, obtained by pole placement and scheduled according to the vehicle state, causes the car to exhibit uniform dynamic behaviour as its speed increases. An additional control loop augments the steering angle of the front wheels, using actuators which form part of a steer-by-wire system, to correct for errors in the lateral position and heading angle for which the force/velocity control loop does not account. The control system is evaluated in simulation experiments which show that the performance requirements are met over a wide range of velocities.
More than 90 percent of all traffic accidents are caused by human error and their involvement in different activities while driving. Therefore we have proposed an Autonomous Vehicle Collision Prevention System. The system is capable to apply Brakes (B) of Vehicle autonomously on time to minimize the risk of destruction. It involves Fuzzy logic based software simulation results comparing with mathematical Mamdani model. This system consists of three inputs and one output. These inputs are DBV (Distance between Vehicles), VS (Vehicle Speed) and SFC (Static Friction Coefficient), one output is B (Brakes). MATLAB based software simulation results of the system and mathematically modeled results are comparing to generate the difference error. Such systems allow Vehicle to apply Brakes (B) according to the situation needed in case of driver negligence.
In this paper a modern gain-scheduling methodology is proposed which exploits recently developed velocity-based techniques to resolve many of the deficiencies of classical gain-scheduling approaches (restriction to near equilibrium operation, to slow rate of variation). This is achieved while maintaining continuity with linear methods and providing an open design framework (any linear synthesis approach may be used) which supports divide and conquer design strategies. The application of velocity-based gain-scheduling techniques is demonstrated in application to a demanding, highly nonlinear, missile control design task. Scheduling on instantaneous incidence (a rapidly varying quantity) is well-known to lead to considerable difficulties with classical gain-scheduling methods. It is shown that the methods proposed here can, however, be used to successfully design an effective and robust gain-scheduled controller.
A family of velocity-based linearizations is proposed for a nonlinear system. In contrast to the conventional series expansion linearization, a member of the family of velocity-based linearizations is valid in the vicinity of any operating point, not just an equilibrium operating point. The velocity-based linearizations facilitate dynamic analysis far from the equilibrium operating points and enable the transient behaviour of the nonlinear system to be investigated. Using velocity-based linearizations, stability conditions are derived for both smooth and non-smooth nonlinear systems which avoid the restrictions to trajectories lying within an unnecessarily (perhaps excessively) small neighbourhood about the equilibrium operating points inherent in existing frozen-input theory. For systems where there is no restriction on the rate of variation the velocity-based linearization analysis is global in nature. The analysis techniques developed, although quite general, are motivated by the gain-scheduling design approach and have the potential for direct application to the analysis of gain-scheduled systems.