Robust model predictive controller of intelligent networked automobile considering communication time delay

Abstract

The invention discloses a robust model prediction controller of an intelligent networked automobile considering communication time delay. The robust model prediction controller comprises the following steps: constructing a vehicle dynamic model, constructing a secondary optimization performance index according to comprehensive optimization of traffic smoothness, safety and fuel economy, and designing a state feedback control law to enable a closed-loop system to be asymptotically stable. In an intelligent network connection environment, vehicles can obtain information of positions, speeds, accelerations and the like of other vehicles and traffic signal information through V2V and V2I communication, and in order to solve the problem of multi-vehicle collaborative optimization of a motorcade passing through urban signal lamp intersections in the presence of communication time delay, a discrete time delay model of the motorcade on a single lane is firstly established; fuel economic performance, traffic smoothness and safety are used as optimization targets; the robust model prediction controller is solved by taking the fuel economy, the traffic fluency and the safety as optimization objectives and utilizing a linear matrix inequality technology and a min-max model prediction control method, so that the robust stability of the system and the optimization of the target performance are ensured.

Description

technical field [0001] The invention relates to the technical field of intelligent network connection, in particular to a robust model predictive controller for intelligent network connection vehicles considering communication delay. Background technique [0002] Intelligent networked vehicles are the combination of intelligent vehicles and networked vehicles, which can bring people a safer, energy-saving, environmentally friendly and convenient transportation experience. It is the future development direction widely recognized internationally at this stage. It has become an inevitable trend. In the environment of intelligent network connection, vehicles can exchange position, speed, acceleration and other information with other vehicles through V2V communication, and can also communicate with drive test units through V2I communication to obtain information such as traffic signals. [0003] In the urban traffic environment, traffic lights set at intersections for safety reas...

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Problems solved by technology

[0004] However, most of the research is in an ideal environment, without considering various uncertainties of the system. In the real environment, communication delay is inherent in a networked environment, which may lead to a decrease in the control performance of CAV, or even It will endanger driving safety. In the existing research considering communication delay, the main research scenario is still the basic fleet cruise control. Only the tracking performance of the vehicle is considered, and the fuel economy and traffic smoothness of the fleet are rarely considered. Optimization

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