A Remote Control Strategy for an Autonomous Vehicle with Slow Sensor Using Kalman Filtering and Dual-Rate Control

Abstract

This work presents a novel remote control solution for an Autonomous Vehicle (AV), where the system structure is split into two sides. Both sides are assumed to be synchronized and linked through a communication network, which introduces time-varying delays and packet disorder. An Extended Kalman Filter (EKF) is used to cope with the non-linearities that appear in the global model of the AV. The EKF fuses the data provided by the sensing devices of the AV in order to estimate the AV state, reducing the noise effect. Additionally, the EKF includes an h-step-ahead state prediction stage, which, together with the consideration of a packet-based control strategy, enables facing the network-induced delays. Since the AV position is provided by a camera, which is a slow sensing device, a dual-rate controller is required to achieve certain desired (nominal) dynamic control performance. The use of a dual-rate control framework additionally enables saving network bandwidth and deals with packet disorder. As the path-tracking control algorithm, pure pursuit is used. Application results show that, despite existing communication problems and slow-rate measurements, the AV is able to track the desired path, keeping the nominal control performance.

A High-Speed Optical Remote-Control Switch Based on Giant Persistent Photoconductivity

“…The remote controls are based on the concept of a wireless switch, composed of a transmitter (remote controller) and a receiver (working device); the controller sends out an encoded signal and the receiver takes/decodes the signal for carrying out the requested commands. − In general, the signal from the transmitter is embedded with the radio or the infrared electromagnetic waves and a typical working distance of the switch, i.e., control range, is of few tens of meters. When the incoming signal from the transmitter is too weak to be processed, the internal amplification unit has to be added to the receiver, which can delay the processing time.…”

A QFT approach to robust dual‐rate control systems

“…With these restrictions is not viable to keep and ideal single frequency in the control loop. In the last years, remote trajectory control of autonomous vehicles 8,9 and efficient energy saving in networked based control systems [10][11][12] also required the use of MR systems. In every these cases, the control problem is that with the mentioned restricted frequency of measurement, far away from the ideal one, is not possible to assure the correct performance of the system.…”

Adaptive-Neuro-Fuzzy-Based Information Fusion for the Attitude Prediction of TBMs

“…The Kalman filter [ 24 , 25 , 26 , 27 ] is one of the most widely used methods because of its simplicity and effectiveness. A Kalman-based approach [ 27 ] could be used to estimate the state and force of a rotating helicopter blade.…”