1,399 research outputs found
Stabilizing Stochastic Predictive Control under Bernoulli Dropouts
This article presents tractable and recursively feasible optimization-based
controllers for stochastic linear systems with bounded controls. The stochastic
noise in the plant is assumed to be additive, zero mean and fourth moment
bounded, and the control values transmitted over an erasure channel. Three
different transmission protocols are proposed having different requirements on
the storage and computational facilities available at the actuator. We optimize
a suitable stochastic cost function accounting for the effects of both the
stochastic noise and the packet dropouts over affine saturated disturbance
feedback policies. The proposed controllers ensure mean square boundedness of
the states in closed-loop for all positive values of control bounds and any
non-zero probability of successful transmission over a noisy control channel
Optimal Sequence-Based Control of Networked Linear Systems
In Networked Control Systems (NCS), components of a control loop are connected by data networks that may introduce time-varying delays and packet losses into the system, which can severly degrade control performance. Hence, this book presents the newly developed S-LQG (Sequence-Based Linear Quadratic Gaussian) controller that combines the sequence-based control method with the well-known LQG approach to stochastic optimal control in order to compensate for the network-induced effects
Feedback and time are essential for the optimal control of computing systems
The performance, reliability, cost, size and energy usage of computing systems can be improved by one or more orders of magnitude by the systematic use of modern control and optimization methods. Computing systems rely on the use of feedback algorithms to schedule tasks, data and resources, but the models that are used to design these algorithms are validated using open-loop metrics. By using closed-loop metrics instead, such as the gap metric developed in the control community, it should be possible to develop improved scheduling algorithms and computing systems that have not been over-engineered. Furthermore, scheduling problems are most naturally formulated as constraint satisfaction or mathematical optimization problems, but these are seldom implemented using state of the art numerical methods, nor do they explicitly take into account the fact that the scheduling problem itself takes time to solve. This paper makes the case that recent results in real-time model predictive control, where optimization problems are solved in order to control a process that evolves in time, are likely to form the basis of scheduling algorithms of the future. We therefore outline some of the research problems and opportunities that could arise by explicitly considering feedback and time when designing optimal scheduling algorithms for computing systems
Switched Stackelberg game analysis of false data injection attacks on networked control systems
summary:This paper is concerned with a security problem for a discrete-time linear networked control system of switched dynamics. The control sequence generated by a remotely located controller is transmitted over a vulnerable communication network, where the control input may be corrupted by false data injection attacks launched by a malicious adversary. Two partially conflicted cost functions are constructed as the quantitative guidelines for both the controller and the attacker, after which a switched Stackelberg game framework is proposed to analyze the interdependent decision-making processes. A receding-horizon switched Stackelberg strategy for the controller is derived subsequently, which, together with the corresponding best response of the attacker, constitutes the switched Stackelberg equilibrium. Furthermore, the asymptotic stability of the closed-loop system under the switched Stackelberg equilibrium is guaranteed if the switching signal exhibits a certain average dwell time. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method in this paper
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