Event-based networked predictive control for networked control systems subject to two-channel delays

Sequential output information based predictive control for event-triggered networked control systems

In a Networked Control System (NCS), event-triggering is often used to reduce the number of network transmission instances and improve network usage. This paper considers transmitting output data rather than the estimated state for such event-triggered schemes. Output transmission facilitates efficient transmission by reducing the size of the packets sent over the network. However, since the state observer utilizes delayed information output transmission deteriorates system performance and requires improved observer-based prediction schemes for closed-loop control. The performance of a new scheme involving the transmission of sequential output information in a single packet to improve the state observer's performance is demonstrated in this paper. A sequential observer is constructed that uses successive output information to better observe the states, and a prediction scheme is used to take care of the delays due to event-triggering, network delays, and dropouts. Further, event-triggering is employed in both the feedback and forward channels. The demonstrated efficacy of this sequential approach in the networked control of an inverted pendulum system and a DC motor system emphasizes its potential as a practical solution for improved control in NCSs, particularly in the face of network constraints and communication challenges.

Predictive control for networked high-order fully actuated systems subject to communication delays and external disturbances

This research is concerned with an output tracking problem for networked high-order fully actuated (NHOFA) systems subject to communication delays and external disturbances, where communication delays occur in sensor to network node and network node to actuator. A HOFA system model, as a novel system representation, is applied to establish the dynamics of networked control systems (NCSs). Accordingly, a disturbance observer based HOFA predictive control approach is proposed to address this problem. In the proposed approach, a disturbance observer is utilized to cope with the external disturbances, and then a local HOFA feedback with disturbance compensation is designed to adjust the closed-loop system performances. Further, a Diophantine Equation is applied to establish an incremental HOFA (IHOFA) prediction model to substitute a reduced-order prediction model, such that multi-step ahead predictions are derived to minimize a cost function involving the optimization of tracking performance and the compensation of network-induced communication delays. A necessary and sufficient criterion is given to discuss the stability and tracking performance of closed-loop NHOFA systems, it is simple to use in system analysis and extend in practice. The availability of the proposed approach is demonstrated via simulated and experimental results for tracking control of air-bearing spacecraft (ABS) simulator.

Cloud-based predictive formation control of networked multi-agent system and its application to air bearing spacecraft simulators

This paper studies a class of networked multi-agent systems with communication delays. A centralized cloud predictive control protocol is proposed to realize formation control of multiple agents and especially the predictive method is introduced to actively compensate for the delays in the network. The analysis of closed-loop networked multi-agent systems provides the necessary and sufficient condition of stability and consensus. Finally, the proposed cloud-based predictive formation control scheme is verified by its application to 3-degree-of-freedom air-bearing spacecraft simulators platform. The results show that the scheme can effectively compensate for the delays in the forward channel and the feedback channel and can be applied to the networked multi-agent systems well.

On Designing the Event-Triggered Multistep Model Predictive Control for Nonlinear System Over Networks With Packet Dropouts and Cyber Attacks

In this article, the event-triggered multistep model predictive control for the discrete-time nonlinear system over communication networks under the influence of packet dropouts and cyber attacks is studied. First, the interval type-2 Takagi-Sugeno fuzzy model is applied to express the discrete-time nonlinear system and an event-triggered mode, which is capable of determining whether the sampled signal ought to be delivered into the unreliable network, is designed to economize communication resources. Second, two Bernoulli processes are introduced to represent the randomly happening packet dropouts in the unreliable network and the randomly occurring deception attacks on the actuator side from the adversaries. Third, under the assumption that the system states are unmeasurable, a multistep parameter-dependent model predictive controller is synthesized via optimizing one series of feedback laws for a given period of time, which leads to improved control performance than that of the one-step approach. Moreover, the results on the recursive feasibility and closed-loop stability related to the networked system are achieved, which explicitly consider the external disturbance and input constraint. Finally, simulation experiments on the mass-spring-damping system are carried out to illustrate the rationality and effectiveness of the provided control strategy.

CAN-Based Vibration Control for Networked Vehicle Active Suspension with Both Network-Induced Delays and Packet-Dropouts

Ride comfort and driving safety are highly vulnerable to the undesirable excessive vibrations caused by road surface irregularities and the imperfect in-vehicle network (IVN). The main contribution of this paper consists of proposing a near-optimal vibration control approach for networked vehicle active suspension under irregular road excitations in a discrete-time domain, in which the uncertain time delay and packet dropout in CAN are taken into consideration. More specially, by virtue of two buffers of the sensor-to-controller network channel and the controller-to-actuator network channel in CAN, by introducing a designed state-transformation-based method, the original vibration control problem under the constraints of the irregular road excitations and imperfect CAN is transformed into a two-point boundary value (TPBV) problem without advanced and delayed items. After that, the near-optimal vibration control approach is presented to isolate the vehicle body from the road excitations and compensate the time delay and packet dropout from CAN synchronously. The stability condition of the networked vehicle active suspension under the proposed vibration controller is obtained based on the Lyapunov function. In numerous scenarios with different road roughnesses and network-induced time delays and packet dropouts, the simulation results illustrate the effectiveness and superiority of the proposed near-optimal vibration controller.