Wireless Feedback Control With Variable Packet Length for Industrial IoT

This paper integrates the IEEE 802.11 g ad-hoc wireless network and the control area network (CAN) in the present network control systems (NCS) or wireless - NCS (WNCS). Both the TCP and the CAN protocols are adopted as the communication gateway in a remote control system. The time delay between the application layer of the client and the application layer of the remote control target has been measured and analyzed in this paper. Experimental results on an AC 400 W servo motor indicate that the communication jam mainly causes the instability due to the induced time delay. In this paper, by applying the adaptive Smith predictor with the switching sampling time, satisfactory control performance of WNCS can be obtained even though the time delay seriously increases. Moreover, the feasibility of the proposed WNCS has been proven through experimental results.

Wireless networked control system (WNCS) is given profound attention because of dynamic, flexibility and inexpensiveness. However, it is difficult to use a single simulator to simulate a WNCS which is a hybrid system. A co-simulation framework based on OPNET, Matlab and C++ is presented to capture both the system dynamics and communication events and depict the real WNCS accurately. MATLAB is good for simulating the mathematical modeling and feedback control, while OPNET is apt at simulating the WLAN communication behavior. The co-simulation framework can help WNCS designer understand and improve the performance of the WNCS.

This article considers a wireless networked control system (WNCS) consisting of a dynamic system to be controlled (i.e., a plant), a sensor, an actuator, and a remote controller for mission-critical Industrial Internet of Things (IIoT) applications. A WNCS has two types of wireless transmissions, i.e., the sensor’s measurement transmission to the controller and the controller’s command transmission to the actuator. In the literature of WNCSs, the controllers are commonly assumed to work in a full-duplex (FD) mode by default, i.e., being able to simultaneously receive the sensor’s information and transmit its own command to the actuator. In this article, we consider a practical half-duplex (HD) controller, which introduces a novel transmission-scheduling problem for WNCSs. A frequent scheduling of sensor’s transmission results in a better estimation of plant states at the controller and thus a higher quality of control command, but it leads to a less frequent/timely control of the plant. Therefore, considering the overall control performance of the plant in terms of its average cost function, there exists a fundamental tradeoff between the sensor’s and the controller’s transmissions. We formulate a new problem to optimize the transmission-scheduling policy for minimizing the long-term average cost function. We derive the necessary and sufficient condition of the existence of a stationary and deterministic optimal policy that results in a bounded average cost in terms of the transmission reliabilities of the sensor-to-controller and controller-to-actuator channels. Also, we derive an easy-to-compute suboptimal policy, which notably reduces the average cost of the plant compared to a naive alternative-scheduling policy.

Applications of control systems on wireless networks have been widely utilized due to their mobility. However, many Wireless Networked Control Systems (WNCS) may not cooperate with each other in order to share a limited amount of network bandwidth. Consequently, these agents may manipulate the resource in their own benefit and selfish behavior. Nevertheless, existing dynamic allocation methods may not lead to equilibrium of all network-based control system satisfactions. This paper presents a decentralized auction-based dynamic bandwidth allocation methodology based on mechanism design and game theory to allocate bandwidths of WNCS which enforces WNCS on the same network to request a bandwidth with actual requirement. The proposed mechanism results has proofed an actual bandwidth requirement is the dominant strategy and the exceed bandwidth requirement cannot provide the higher utility than the actual bandwidth requirement. The total utility is the solutions of maximized social welfare.

Wireless networked control systems (WNCS) over mobile ad hoc network (MANET) is a new area of research and has many potential applications, for instance, military or rescue missions, exploring hazardous environments, and so on. For performance evaluation, researchers mostly rely on computer simulations as WNCS experiments are expensive to execute. It will generate a significant benefit to conduct performance analysis of WNCS over MANET using co-simulation that utilises SIMULINK and OPtimised Network Engineering Tool (OPNET) to simulate plant/controller behaviour and the MANET, respectively. Previous conference papers by the authors reported the initial SIMULINK-OPNET co-simulation for only one network size. Here the authors present an extention of their previous work, and presents the SIMULINK-OPNET co-simulation, methodology and comprehensive simulation results that have not been reported previously. It also considers the impact of five network sizes with stationary and mobile nodes. The proposed SIMULINK-OPNET co-simulation is applied to WNCS over MANET using a realistic wireless communication model. It investigates the impact of network data rates, node mobility, the packet delay, packet drop on the system stability and performance.

In order to effectively restrain the impact of network delays for wireless networked control systems (WNCS), aiming to time-variant, random and uncertain network delays and controlled plant might be time-variant or nonlinear, as well as Smith predictor models might be imprecise, we propose a novel approach that modified Smith predictor combined with fuzzy immune self-regulating PID control for the WNCS. Because modified Smith predictor does not include network delay models, therefore, it is no need for measuring on line, identifying or estimating network delays, thus it is applicable to some occasions that network delays are larger than one, even tens of sampling periods. Based on IEEE 802.11 b/g (WLAN), the results of simulation experiment show validity of the control scheme and improvement in dynamic performance and robustness of the WNCS.

The integration of wireless communication and control systems revealed wireless networked control systems (WNCSs). One fundamental problem in WNCSs is to have a wide coverage area. For the first time in the literature, we address this problem and we obtain the maximum coverage area by solving an optimization problem. In this technical note, we consider a WNCS where the output sensor measurements are transmitted over separate heterogeneous multi-hop wireless ad-hoc subnetworks. The observation process is divided into N parts and the system state is estimated using the Kalman filter. We present the critical arrival probability for a sensor measurement packet such that if the packet arrival probability is larger than the critical value, it is guaranteed that the estimator of the WNCS converges. We derive the maximum total coverage area of the heterogeneous wireless subnetworks having maximum cost-efficiency under the constraint of the convergence of the WNCS estimator.

Markovian jumping systems have arisen naturally in the mathematical modeling of phenomena spanning disciplines in the social sciences, natural sciences, and engineering. This kind of stochastic dynamical systems can be employed to model the dynamics when parameters are subject to random abrupt changes due to sudden environment changes, subsystem switching, system noises, executor faults, and so forth. Much attention has been given to modeling, optimization, and real applications of such stochastic dynamical systems in the literature in recent years. As the advanced control and optimization will provide a basis for the design and application of such stochastic systems, these advanced techniques would result in substantial and sustainable benefits. The accepted papers in this special issue include stochastic stability, stabilization, stochastic control optimization, system modeling and identification methods, predictive control, signal processing, robust filtering, multiagent systems, networked control systems, time-delayed systems, neural networks, the Takagi-Sugeno fuzzy systems, simulated annealing, and fault detection methods.

Wireless Network Control Systems (WNCSs) have been developed and deployed in many applications because of the flexibility afforded by the wireless communications medium in accommodating the control loop. In this paper, we examine a wide area WNCS using LTE as the wireless fabric. We introduce a novel concept known as “reflection” which is a subscription model that allows an LTE eNodeB to inform certain nodes in a group about low level radio signalling from certain other nodes in the group before any application data has been sent. The mean Round Trip Time (RTT) for control in an LTE based wide area WNCS which is enhanced for reflection is reduced by at least 6ms compared to a standard LTE based wide area WNCS. This is demonstrated using an OPNET simulation model that compares a reflection based architecture with a reference architecture. The technique has applications in Smart Grid control applications (such as Fault Detection and Isolation) and in other vertical industries in which WNCSs may be relevant.

The unprecedented growth of industrial Internet of Things applications requires the evolution of wireless networked control system (WNCS). WNCSs are becoming the fundamental infrastructure technologies for critical wireless control applications due to the main benefits of the reduced deployment and maintenance cost, as well as the enhanced flexibility and safety. However, independent designs between communication and control without considering their tight interaction in conventional WNCS lead to poor overall system performance and efficiency. Co-designs are expected to achieve the target control performance while improving the wireless resource efficiency. In this paper, by considering how to allocate wireless resource while guaranteeing control performance, a co-design framework is established based on the finite-time wireless system identification (WSI) - a fundamental problem in systems theory and intelligent control. To this end, two design problems are investigated aiming at maximizing the communication throughput or minimizing the power consumption while guaranteeing the WSI performance. In the former design, the joint optimization of power and channel allocations leads to a non-convex integer combinatorial problem, which is iteratively solved by optimizing the power allocation via Lagrangian method and obtaining the optimal channel allocation via Hungarian algorithm. The minimum number of data samples for guaranteeing the WSI accuracy under confidence level is further derived by exploiting the relationship between WSI accuracy and the number of state sampling processes, which leads to the maximum throughput with respect to both the communication and control processes. In the latter design for energy-efficient WSI, by exploiting the relationship between the power consumption and channel allocation given the WSI performance requirement, the optimization problem can be simplified and solved by Hungarian algorithm. Simulations are conducted to verify the performance of the proposed solutions.

In this paper, we study a wireless networked control system (WNCS) with $N \ge 2$ sub-systems sharing a common wireless channel. Each sub-system consists of a plant and a controller and the control message must be delivered from the controller to the plant through the shared wireless channel. The wireless channel is unreliable due to interference and fading. As a result, a packet can be successfully delivered in a slot with a certain probability. A network scheduling policy determines how to transmit those control messages generated by such $N$ sub-systems and directly influences the transmission delay of control messages. We first consider the case that all sub-systems have the same sampling period. We characterize the stability condition of such a WNCS under the joint design of the control policy and the network scheduling policy by means of $2^N$ linear inequalities. We further simplify the stability condition into only one linear inequality for two special cases: the perfect-channel case where the wireless channel can successfully deliver a control message with certainty in each slot, and the symmetric-structure case where all sub-systems have identical system parameters. We then consider the case that different sub-systems can have different sampling periods, where we characterize a sufficient condition for stability.

Energy efficient robust scheduling of periodic sensor packets for discrete rate based wireless networked control systems

Jamming attacks on wireless networked control systems are investigated for the scenarios where the system dynamics face exogenous disturbance. In particular, the control input packets are assumed to be transmitted from a controller to a remotely located linear plant over an insecure wireless communication channel that is subject to jamming attacks. The time-varying likelihood of transmission failures on this channel depends on the power of the jamming interference signal emitted by an attacker. We show that jamming attacks can prevent stability when the system faces disturbance, even if the attacked system without disturbance is stable. We also show that stability under jamming and disturbance can be achieved if the average jamming interference power is restricted in a certain way that we characterize in this article. We illustrate our results on an example networked control system with a fading wireless channel, where the outage probability is affected by jamming attacks.

This paper aims at time-variant or uncertain wireless network delay in the wireless networked control systems (WNCS), a new Smith dynamic predictor is proposed.Because new Smith dynamic predictor hides predictor model of the network delay into real transmission process of the network data, further the network delay no longer need to be measured, identified or estimated on-line. It is applicable twosome occasions that wireless network delay is random, time variant or uncertain, possibly large compared to one, even tens sampling periods, at the same time, there are some data dropouts in closed loop. Based on IEEE 802.15.4 (ZigBee), the results of simulation show validity of the compensation scheme in the WNCS, and indicate that system has better dynamic performance and robustness.

There is a strong trend towards wireless networked Real-Time Control Systems. However, a variety of factors such as the variability of wireless channel capacities, multi-path fading, and ambient interference make it extraordinarily difficult to design and implement Wireless Control Systems (WCSs). To attack the uncertainty in available communication resource in WCSs, this chapter presents an Adaptive Feedback Scheduling scheme that takes advantage of the methodology of cross-layer design. The proposed approach exchanges information across the physical layer and the application layer in the presence of noise interference and link transmission rate variations. The overall QoC is guaranteed through controlling the deadline miss ratio of control loops. Design parameters of the feedback scheduler are adapted to dynamic changes in wireless channel capacity. To further improve the feedback scheduling performance, an event-driven invocation mechanism for feedback schedulers is suggested. Simulation results demonstrate that this approach is efficient to deal with channel capacity variations and noise interference, thus providing an enabling technology for wireless control in dynamic environments. It is also argued that in this context event-driven invocation mechanism improves the performance of the feedback scheduling system.KeywordsSampling PeriodTransmission RateMedium Access ControlControl PerformanceMedium Access Control ProtocolThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.