Optimal scheduling and control for constrained multi-agent networked control systems

In this paper, we study optimal control and communication schedule co-design for multi-agent networked control systems, with assuming shared parallel communication channels and uncertain constrained linear time-invariant discrete-time systems. To that end, we specify the communication demand for each system using an associated robust control invariant set and reachability analysis. We use these communication demands and invariant sets to formulate tube-based model predictive control and offline/online communication schedule co-design problems. Since the scheduling part includes an infinite dimension integer problem, we propose heuristics to find suboptimal solutions that guarantee robust constraints satisfaction and recursive feasibility. The effectiveness of our approach is illustrated through numerical simulations

Stochastic optimal adaptive controller and communication protocol design for networked control systems

Networked Control System (NCS) is a recent topic of research wherein the feedback control loops are closed through a real-time communication network. Many design challenges surface in such systems due to network imperfections such as random delays, packet losses, quantization effects and so on. Since existing control techniques are unsuitable for such systems, in this dissertation, a suite of novel stochastic optimal adaptive design methodologies is undertaken for both linear and nonlinear NCS in presence of uncertain system dynamics and unknown network imperfections such as network-induced delays and packet losses. The design is introduced in five papers. In Paper 1, a stochastic optimal adaptive control design is developed for unknown linear NCS with uncertain system dynamics and unknown network imperfections. A value function is adjusted forward-in-time and online, and a novel update law is proposed for tuning value function estimator parameters. Additionally, by using estimated value function, optimal adaptive control law is derived based on adaptive dynamic programming technique. Subsequently, this design methodology is extended to solve stochastic optimal strategies of linear NCS zero-sum games in Paper 2. Since most systems are inherently nonlinear, a novel stochastic optimal adaptive control scheme is then developed in Paper 3 for nonlinear NCS with unknown network imperfections. On the other hand, in Paper 4, the network protocol behavior (e.g. TCP and UDP) are considered and optimal adaptive control design is revisited using output feedback for linear NCS. Finally, Paper 5 explores a co-design framework where both the controller and network scheduling protocol designs are addressed jointly so that proposed scheme can be implemented into next generation Cyber Physical Systems --Abstract, page iv

Contention-resolving model predictive control for coupled control systems with shared resources

Priority-based scheduling strategies are often used to resolve contentions in resource constrained control systems. Such scheduling strategies inevitably introduce time delays into controls, which may degrade the performance or sabotage the stability of control systems. Considering the coupling between priority assignment and control, this thesis presents a novel method to co-design priority assignments and control laws for each control system, which aims to minimize the overall performance degradation caused by contentions. The co-design problem is formulated as a mixed integer optimization problem with a very large search space, rendering difficulty in computing the optimal solution. To solve the problem, we develop a contention-resolving model predictive control method to dynamically assign priorities and compute an optimal control. The priority assignment can be generated using a sample-based approach without excessive demand on computing resources, and all possible priority combinations can be presented by a decision tree. We present sufficient and necessary conditions to test the schedulabilty of the generated priorities assignments when constructing the decision tree, which guarantee that the priority assignments in the decision tree always lead to feasible solutions. The optimal controls can then be computed iteratively following the order of the generated feasible priorities. The optimal priority assignment and control design can be determined by searching the lowest cost path in the decision tree. With the fundamental assumptions required in real-time scheduling, the solution computed by the contention-resolving model predictive control is proved to be globally optimal. The effectiveness of the presented method is verified through simulation in three real-world applications, which are networked control systems, traffic intersection management systems, and human-robot collaboration systems. The performance of our method is compared with the well-known and most commonly used scheduling methods in these applications and demonstrate significant improvements using our method.Ph.D

Control and Communication-Schedule Co-design For Networked Control Systems

In a networked control system (NCS), the control loop is closed through a communication medium. This means that sensor measurements and/or control signals can be exchanged through a communication link. NCSs have many benefits, such as wiring reduction (elimination in the case of wireless communication), installation cost reduction, and simplification of upgrades and restructuring. However, network congestion, impairments of the wireless links (such as bandwidth limitations, packet losses, delays, and noises) may degrade system performance and even cause instability. These issues have motivated a great deal of research over the past 20 years and have given rise to a number of approaches to prevent congestion and compensate for delays and/or packet losses.An interesting class of NCSs that has not received enough attention is an NCS whose systems are uncertain and subject to state and inputs hard constraints.These hard constraints may stem from the system itself, its environment, or be proposed by the designer in order to guarantee safety or a certain performance.The contribution of this thesis is introducing a design framework that guarantees robust constraint satisfaction for a class of multi-agent NCSs with a shared communication medium that is subject to bandwidth limitation and prone to packet losses.The proposed framework is built upon reachability analysis to determine the communication demand for each system such that local constraints are satisfied and scheduling techniques to guarantee satisfaction of the communication demands. The thesis explores offline and online scheduling designs under various communication topologies, optimal control designs under state and output feedback, and scheduling and control co-design for NCSs with hard constraints

Optimal co-design of control, scheduling and routing in multi-hop control networks

A Multi-hop Control Network consists of a plant where the communication between sensors, actuators and computational units is supported by a (wireless) multi-hop communication network, and data flow is performed using scheduling and routing of sensing and actuation data. Given a SISO LTI plant, we will address the problem of co-designing a digital controller and the network parameters (scheduling and routing) in order to guarantee stability and maximize a performance metric on the transient response to a step input, with constraints on the control effort, on the output overshoot and on the bandwidth of the communication channel. We show that the above optimization problem is a polynomial optimization problem, which is generally NP-hard. We provide sufficient conditions on the network topology, scheduling and routing such that it is computationally feasible, namely such that it reduces to a convex optimization problem.Comment: 51st IEEE Conference on Decision and Control, 2012. Accepted for publication as regular pape

Cross-Layer Adaptive Feedback Scheduling of Wireless Control Systems

There is a trend towards using wireless technologies in networked control systems. However, the adverse properties of the radio channels make it difficult to design and implement control systems in wireless environments. To attack the uncertainty in available communication resources in wireless control systems closed over WLAN, a cross-layer adaptive feedback scheduling (CLAFS) scheme is developed, which takes advantage of the co-design of control and wireless communications. By exploiting cross-layer design, CLAFS adjusts the sampling periods of control systems at the application layer based on information about deadline miss ratio and transmission rate from the physical layer. Within the framework of feedback scheduling, the control performance is maximized through controlling the deadline miss ratio. Key design parameters of the feedback scheduler are adapted to dynamic changes in the channel condition. An event-driven invocation mechanism for the feedback scheduler is also developed. Simulation results show that the proposed approach is efficient in dealing with channel capacity variations and noise interference, thus providing an enabling technology for control over WLAN.Comment: 17 pages, 12 figures; Open Access at http://www.mdpi.org/sensors/papers/s8074265.pd