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.

In this paper, a novel delay-independent control structure for a networked control system (NCS) is proposed, where packet-based control strategies with predictor-based and dual-rate control techniques are integrated. The control solution is able to cope with some networked communication problems such as time-varying delays, packet dropouts and packet disorder. In addition, the proposed approach enables to reduce network load, and usage of connected devices, while maintaining a satisfactory control performance. As a delayindependent control solution, no network-induced delay measurement is needed for controller implementation. In addition, the control scheme is applicable to open-loop unstable plants. Control system stability is ensured in terms of linear matrix inequalities (LMIs). Simulation results show the main benefits of the control approach, which are experimentally validated by means of a Cartesian-robot-based test-bed platform.

This paper introduces a packet-based dual-rate control strategy to face time-varying network-induced delays, packet dropouts and packet disorder in a Networked Control System. Slow-rate sensing enables to achieve energy saving by reducing network load. In addition, choosing a slower sensing period than the longest round-trip time delay can avoid packet disorder. On the other hand, a slow-rate sensing usually degrades control performance in a conventional control framework. Therefore, including dual-rate control techniques can be useful to maintain the desired performance, since the controller is able to generate a fast-rate control signal from a slow-rate sensing signal. A dual-rate PID controller is used, which can be split into two parts: a slow-rate PI controller is located at the remote side (with no permanent communication to the plant) and a fast-rate PD controller, at the local side (close to the plant, sensor, and inside the actuator, which can offer a low computation power). In addition, at the remote side, where a powerful computation device is located, a prediction stage is included in order to generate the packet of future, estimated slow-rate control actions to be sent to the local side. At this side, these actions are converted to fast-rate ones and used when a packet does not arrive due to the network-induced delay or due to occurring dropouts. The control proposal is able to reach the nominal (no-dropout, no-delay) performance despite the existence of time-varying delays and packet dropouts. Via real-time control for a Cartesian robot, results clearly reveal the superiority of the control approach compared to a previous authors\' proposal, where the time-varying delays are faced by means of a gain scheduling control strategy.