Stabilization of model-based networked control systems

A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network traffic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.This work was supported by Portuguese funds through the CIDMA - Center for Research and Development in Mathematics and Applications, and the Portuguese Foundation for Science and Technology (“FCT - Fundação para a Ciência e a Tecnologia”), within project UID/MAT/04106/2013.info:eu-repo/semantics/publishedVersio

Stabilization of networked control systems via dynamic output-feedback controllers

This paper investigates the problem of stabilization of networked control systems via dynamic output-feedback controllers. The physical plant and the dynamic controller are in continuous time, and a communication channel exists between the output of the physical plant and the input of the dynamic controller. Three important communication features are considered: measurement quantization, signal transmission delay, and data packet dropout, which appear typically in a networked environment. Attention is focused on the design of dynamic output-feedback controllers which ensure asymptotic stability of the closed-loop systems. Linear matrix inequality (LMI)-based conditions are formulated for the existence of admissible controllers. If these conditions are satisfied, a desired controller can be readily constructed. A satellite system is used to illustrate the applicability and effectiveness of the proposed controller design method.published_or_final_versio

Tradeoffs and limitations in Networked Control Systems

Control and communication have been increasingly studied together in the recent past. The \u27Satellite - Ground Controller\u27 is a classic example of a remote control problem. Another closely related topic of study is control over an unreliable communication network and its applications seem to grow continuously. Networked Control Systems (NCS) is a rapidly growing research topic and examples of practical significance include multiple vehicle coordination, air-traffic control, and Micro-Electro-Mechanical Systems (MEMS). The work presented consists of two problems (1) The Remote control problem and (2) The Networked control problem. The remote control problem we address is the feedback stabilization of a linear discrete-time plant in feedback with a linear controller via unreliable communication channels. The channels are modeled as analog packet-drop (erasure) channels. Erasure channel is a good model of loss of data packets, typical in large networks like the Internet. We analyze the maximum sustainable erasure on the sensor and actuator channels given a level of erasure on the feedback (Service) channel and synthesize controllers. The networked control problem we address is a special case of spatially invariant plants interconnected through a static network. We consider a circular topology of interconnection and introduce a new notion of Bode sensitivity integral for networks of spatially invariant plants in feedback with static networks and comment on the fundamental limitations of design of such feedback networks

Stabilization of discrete-time systems with time-varying delay using simple lyapunov-krasovskii functional

This thesis studies stabilization of discrete time-delay systems based on Lyapunov-Krasovskii functional. Time-delays frequently occur in various practical systems, such as networked control systems, chemical processes, neural networks, and long transmission lines in pneumatic systems. The different phenomena that cause time-delay are: (a) Time needed to transport mass, energy or information; (b) Time lags get accumulated in great number of low-order systems connected in series; and (c) Sensors, such as analyzers; controllers need some time to implement a complicated control algorithm or process. The presence of delay causes in general performance degradation and may lead to instability within the system First, stability of networked control systems has been studied. Two available stability criteria for linear discrete time systems with interval like time varying delay have been considered. Also a numerical example has been solved and the results of both the stability criteria have been compared. Static output-feedback stabilization of discrete-time system with time-varying delay is studied next. Two stabilization approaches based on the above discussed stability criteria are studied. A numerical example has been solved and simulation results have been obtained for both the approaches. Simulation output indicates that the given stabilization approaches effectively stabilize the system and their performance in terms of achievable delay margin is compared

Stabilization of systems with asynchronous sensors and controllers

We study the stabilization of networked control systems with asynchronous sensors and controllers. Offsets between the sensor and controller clocks are unknown and modeled as parametric uncertainty. First we consider multi-input linear systems and provide a sufficient condition for the existence of linear time-invariant controllers that are capable of stabilizing the closed-loop system for every clock offset in a given range of admissible values. For first-order systems, we next obtain the maximum length of the offset range for which the system can be stabilized by a single controller. Finally, this bound is compared with the offset bounds that would be allowed if we restricted our attention to static output feedback controllers.Comment: 32 pages, 6 figures. This paper was partially presented at the 2015 American Control Conference, July 1-3, 2015, the US

Networked Predictive Control of Uncertain Constrained Nonlinear Systems: Recursive Feasibility and Input-to-State Stability Analysis

Abstract-In this paper, the robust state feedback stabilization of uncertain discrete-time constrained nonlinear systems in which the loop is closed through a packet-based communication network is addressed. In order to cope with model uncertainty, timevarying transmission delays, and packet dropouts (typically affecting the performances of networked control systems), a robust control scheme combining model predictive control with a network delay compensation strategy is proposed in the context of non-acknowledged UDP-like networks. The contribution of the paper is twofold. First, the issue of guaranteeing the recursive feasibility of the optimization problem associated to the receding horizon control law has been addressed, such that the invariance of the feasible region under the networked closed-loop dynamics can be guaranteed. Secondly, by exploiting a novel characterization of regional Input-to-State Stability in terms of time-varying Lyapunov functions, the networked closed-loop system has been proven to be Input-to-State Stable with respect to bounded perturbations

Finite-Time Boundedness and Stabilization of Networked Control Systems with Time Delay

The finite-time control problem of a class of networked control systems (NCSs) with time delay is investigated. The main results provided in the paper are sufficient conditions for finite-time stability via state feedback. An augmentation approach is proposed to model NCSs with time delay as linear systems. Based on finite time stability theory, the sufficient conditions for finite-time boundedness and stabilization of the underlying systems are derived via linear matrix inequalities (LMIs) formulation. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed results

Stability Analysis and Control of Several Classes of Logical Dynamic Systems and the Applications in Game Theory

With the rapid development of complex networks, logical dynamic systems have been commonly used mathematical models for simulating Genetic Regulatory Networks (GRNs) and Networked Evolutionary Games (NEGs), which have attracted considerable attention from biology, economy and many other fields. By resorting to the Semi-Tensor Product (STP) of matrices, logical dynamic systems can be equivalently converted into discrete time linear systems with algebraic forms. Based on that, this thesis analyzes the stability and studies the control design problems of several classes of logical dynamic systems. Moreover, the obtained results are applied to investigate the control and optimization problems of NEGs. The main results of this thesis are the following. • The stability and event-triggered control for a class of k-Valued Logical Networks (KVLNs) with time delays are studied. First, some necessary and sufficient con- ditions are obtained to detect the stability of Delayed k-Valued Logical Networks (DKVLNs). Second, the global stabilization problem under event-triggered control is considered, and some necessary and sufficient conditions are presented for the sta- bilization of Delayed k-Valued Logical Control Networks (DKVLCNs). Moreover, an algorithm is proposed to construct all the event-triggered state feedback controllers via antecedence solution technique. • The robust control invariance and robust set stabilization problems for a class of Mix- Valued Logical Control Networks (MVLCNs) with disturbances are studied. First, a calculation method for the Largest Robust Control Invariant Set (LRCIS) contained in a given set is introduced. Second, based on the Robust Control Invariant Subset (RCIS) obtained, the robust set stabilization of MVLCNs is discussed, and some new results are presented. Furthermore, the design algorithm of time-optimal state feedback stabilizers via antecedence solution technique is derived. • The robust set stability and robust set stabilization problems for a class of Probabilis- tic Boolean Control Networks (PBCNs) with disturbances are studied. An algorithm to determine the Largest Robust Invariant Set (LRIS) with probability 1 of a given set for a Probabilistic Boolean Network (PBN) is proposed, and the necessary and sufficient conditions to detect whether the PBN is globally finite-time stable to this invariant set with probability 1 are established. Then, the PBNs with control inputs are considered, and an algorithm for LRCIS with probability 1 is provided, based on which, some necessary and sufficient conditions for finite-time robust set stabiliza- tion with probability 1 of PBCNs are presented. Furthermore, the design scheme of time-optimal state feedback stabilizers via antecedence solution technique is derived. • The stabilization and set stabilization problems for a class of Switched Boolean Con- trol Networks (SBCNs) with periodic switching signal are studied. First, algebraic forms are constructed for SBCNs with periodic switching signal. Second, based on the algebraic formulations, the stabilization and set stabilization of SBCNs with peri- odic switching signal are discussed, and some new results are presented. Furthermore, constructive procedure of open loop controllers is given, and the design algorithms of switching-signal-dependent state feedback controllers via antecedence solution tech- nique are derived. • The dynamics and control problems for a class of NEGs with time-invariant delay in strategies are studied. First, algebraic forms are constructed for Delayed Networked Evolutionary Games (DNEGs). Second, based on the algebraic formulations, some necessary and sufficient conditions for the global convergence of desired strategy pro- file under a state feedback event-triggered controller are presented. Furthermore, the constructive procedure and the number of all valid event-triggered state feedback controllers are derived, which can make the game converge globally. • The evolutionary dynamics and optimization problems of the networked evolutionary boxed pig games with the mechanism of passive reward and punishment are studied. First, an algorithm is provided to construct the algebraic formulation for the dynamics of this kind of games. Then, the impact of reward and punishment parameters on the final cooperation level of the whole network is discussed

Stabilization of Networked Control Systems under Feedback-based Communication

We study the stabilization of a networked control system (NCS) in which multiple sensors and actuators of a physical plant share a communication medium to exchange information with a remote controller. The plant's sensors and actuators are allowed only limited access to the controller at any one time, in a way that is decided on-line using a feedback-based communication policy. Our NCS model departs from those in previous formulations in that the controller and plant handle communication disruptions by ``ignoring'' (in a sense that will be made precise) sensors and actuators that are not actively communicating. We present an algorithm that provides a complete and straightforward method for simultaneously determining stabilizing gains and communication policies and avoids the computational complexity and limitations associated with some previously proposed models. We introduce three feedback-based scheduling policies that quadratically stabilize the closed-loop NCS while achieving various objectives related to the system's rate of convergence, the priorities of different sensors and actuators, and the avoidance of chattering