Guaranteed‐Cost Consensus Control For High‐Order Linear Swarm Systems

Guaranteed‐cost consensus analysis and design problems for high‐order linear time‐invariant swarm systems are dealt with in this paper. First, a guaranteed‐cost consensus control problem is introduced to obtain a trade‐off design object between consensus regulation performances and control energy consumptions. Then, sufficient conditions for guaranteed‐cost consensus and consensualization are presented respectively, an upper bound of the cost function is determined, and explicit expressions of consensus functions are given, which are independent of interaction topologies of swarm systems. Finally, a numerical example is shown to demonstrate theoretical results.     

Finite‐time guaranteed cost control for Itô Stochastic Markovian jump systems with incomplete transition rates

This paper is concerned with the finite‐time guaranteed cost control problem for stochastic Markovian jump systems with incomplete transition rates. By a mode‐dependent approach (MDA), several new sufficient conditions for the existence of state and output feedback finite‐time guaranteed cost controllers are provided, and the upper bound of cost function is more accurately expressed. Moreover, these results' superiorities are analyzed and shown. A new N‐mode optimization algorithm is given to minimize the upper bound of cost function. Finally, a detailed example is utilized to demonstrate the merit of the proposed results. Copyright © 2016 John Wiley & Sons, Ltd.     

Guaranteed cost consensus for multi‐agent systems with switching topologies

Firstly, guaranteed cost consensus for multi‐agent systems is introduced based on state errors among neighboring agents and control inputs of all agents, where a tradeoff between the consensus regulation performance and the control effort is considered. Then, a sufficient condition for guaranteed cost consensus is given by the state‐space decomposition approach and the Lyapunov method, where an upper bound of the cost function is determined and an approach is proposed to determine the control gain. It is worth mentioning that the criterions for guaranteed cost consensus are only dependent on the maximum eigenvalue of the Laplacian matrices of switching topologies. Finally, numerical simulations are given to demonstrate theoretical results. Copyright © 2014 John Wiley & Sons, Ltd.     

A note on guaranteed cost control for nonlinear stochastic systems with input saturation and mixed time‐delays

ThisIn the system under investigation, the control input is subject to the saturation constraint, and both discrete and distributed time‐delays are taken into consideration. The objective of the addressed problem is to design a state feedback controller such that the resulting closed‐loop system is asymptotically stable in probability and an upper bound is guaranteed on a prespecified quadratic cost function. Sufficient conditions are established for the existence of the desired guaranteed cost control strategy in terms of the solvability of certain Hamilton–Jacobi inequalities. Simulation results demonstrate the correctness and applicability of the proposed control scheme. Copyright © 2017 John Wiley & Sons, Ltd.     

A resilient consensus strategy of near‐optimal control for state‐saturated multiagent systems with round‐robin protocol

In this paper, the resilient consensus strategy design problem is investigated for the time‐varying state‐saturated multiagent systems (MASs). A round‐robin protocol is adopted to schedule the communication network among the MASs for the purpose of preventing the data from collision. In presence of the state‐saturation and gain perturbation phenomena, it is literally impossible to obtain the accurate value of the associate cost function, which describes the consensus performance. As an alternative, an upper bound is derived for the cost function to quantify the consensus performance. Then, the resilient consensus strategy is designed such that this upper bound can be minimized in an iterative manner. The sufficient condition is also provided to guarantee that the upper bound of the cost function exists as time goes to infinity. Finally, a numerical example is provided to illustrate the validity of the proposed methodology.     

Design of non‐fragile guaranteed‐cost repetitive‐control system based on two‐dimensional model

This paper concerns a new method of repetitive control based on two‐dimensional (2D) system theory. First, a 2D model is presented that enables the independent adjustment of control, which happens within a repetition period, and learning, which happens between periods. Next, the problem of designing a repetitive‐control law is formulated as a state‐feedback design problem for the 2D model. An existence condition and a method of designing a robust repetitive‐control law for a plant containing time‐invariant structured uncertainties are established by combining 2D system theory with linear matrix inequalities. Then, based on those results, a non‐fragile guaranteed‐cost repetitive‐control law is derived. The controller gain to be designed is assumed to have additive gain variations. It guarantees that the value of a quadratic performance function is less than a specified upper bound for all admissible uncertainties. The main feature of this approach is that it enables the control action and the learning process to be adjusted independently by the direct tuning of the weighting matrices in the quadratic cost function. Finally, a numerical example demonstrates the validity of this approach. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Guaranteed cost control of uncertain discrete‐time singular Markov jump systems with indefinite quadratic cost

The guaranteed cost control problem for discrete‐time singular Markov jump systems with parameter uncertainties is discussed. The weighting matrix in quadratic cost function is indefinite. For full and partial knowledge of transition probabilities cases, state feedback controllers are designed based on linear matrix inequalities method which guarantee that the closed‐loop discrete‐time singular Markov jump systems are regular, causal and robust stochastically stable, and the cost value has a zero lower bound and a finite upper bound. A numerical example to illustrate the effectiveness of the method is given in the paper. Copyright © 2010 John Wiley & Sons, Ltd.     

Guaranteed cost finite‐time control for semi‐Markov jump systems with event‐triggered scheme and quantization input

In this paper, the guaranteed cost finite‐time control for semi‐Markov jump systems with unknown transition rates is addressed. An event‐triggered scheme is constructed to automatically monitor the data transmission and the input quantization is involved to reduce the cost of control. Different from the existing general transition rates in the semi‐Markov jump systems, the upper and lower bounds of transition rates are not given in advance but obtained through the stability criteria. The stability criteria are established to verify the stochastic finite‐time boundedness of the closed‐loop event‐triggered system and estimate the performance index of the given cost function. A guaranteed cost optimal controller is also proposed to stabilize the considered system. Finally, the vertical take‐off and landing helicopter model is introduced to verify the effectiveness of the main algorithms.     

An LMI approach to output‐feedback‐guaranteed cost control for uncertain time‐delay systems

This paper considers the problem of output‐feedback‐guaranteed cost controller design for uncertain time‐delay systems. The uncertainty in the system is assumed to be norm‐bounded and time‐varying. The time‐delay is allowed to enter the state and the measurement equations. A linear quadratic cost function is considered as a performance measure for the closed‐loop system. Necessary and sufficient conditions are provided for the construction of a guaranteed cost controller. These conditions are given in terms of the feasibility of LMIs which depend on a positive definite matrix and a scaling variable. A numerical algorithm is developed to search for a full order dynamic output‐feedback controller which minimizes the cost bound. Copyright © 2000 John Wiley & Sons, Ltd.     

Robust H2 guaranteed cost fuzzy control for uncertain discrete‐time fuzzy systems via poly‐quadratic Lyapunov functions

In this paper, new approaches regarding H₂ guaranteed cost stability analysis and controller synthesis problems for a class of discrete‐time fuzzy systems with uncertainties are investigated. The state‐space Takagi‐Sugeno fuzzy model with norm‐bounded parameter uncertainties is adopted. Based on poly‐quadratic Lyapunov functions, sufficient conditions for the existence of the robust H₂ fuzzy controller can be obtained in terms of linear matrix inequalities (LMIs). Furthermore, a convex optimization problem with LMI constraints is formulated to design a suboptimal fuzzy controller which minimizes the upper bound on the quadratic cost function. The effectiveness of the proposed design approach is illustrated by two examples. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Guaranteed cost control of distributed parameter networked control systems with time‐varying delay

Distributed parameter networked control systems mean distributed parameter systems are controlled through a network, where the control loops are closed. In this paper, the problem of guaranteed cost and state feedback controller design is investigated for a class of distributed parameter networked control systems. With the network factors, such as transmission delays, data packet dropouts considered, the distributed parameter networked control system is modeled as a linear closed‐loop system with time‐varying delay and uncertain parameters. By selecting an appropriate Lyapunov‐Krasovskii function and using linear matrix inequality (LMI) approach, the controller is designed to render the system stable and it can keep the cost function less than a certain upper value. In addition, numerical simulation is included to demonstrate the theoretical results.     

On delay‐dependent LMI‐based guaranteed cost control of uncertain neutral systems with discrete and distributed time‐varying delays

In this paper, the problem of designing robust guaranteed cost control law for a class of uncertain neutral system with a given quadratic cost function is considered. Based on Lyapunov–Krasovskii functional theory, a delay‐dependent criterion for the existence of guaranteed cost controller is expressed in the form of two linear matrix inequalities (LMIs), which can be solved by using effective LMI toolbox. Moreover, a convex optimization problem satisfying some LMI constraints is formulated to solve a guaranteed cost controller which achieves the minimization of the closed‐loop guaranteed cost. An efficient approach is proposed to design the guaranteed cost control for uncertain neutral systems. Computer software Matlab can be used to solve all the proposed results. Finally, a numerical example is illustrated to show the usefulness of our obtained design method. Copyright © 2006 John Wiley & Sons, Ltd.     

Finite‐Time Guaranteed Cost Control of Caputo Fractional‐Order Neural Networks

In this paper, we investigate the problem of finite‐time guaranteed cost control of uncertain fractional‐order neural networks. Firstly, a new cost function is defined. Then, by using linear matrix inequalities (LMIs) approach, some new sufficient conditions for the design of a state feedback controller which makes the closed‐loop systems finite‐time stable and guarantees an adequate cost level of performance are derived. These conditions are in the form of linear matrix inequalities, which therefore can be efficiently solved by using existing convex algorithms. Finally, two numerical examples are given to illustrate the effectiveness of the proposed method.     

Adaptive fixed‐time fault‐tolerant control for rigid spacecraft using a double power reaching law

In this paper, an adaptive fixed‐time fault‐tolerant control scheme is presented for rigid spacecraft with inertia uncertainties and external disturbances. By using an inverse trigonometric function, a novel double power reaching law is constructed to speed up the state stabilization and reduce the chattering phenomenon simultaneously. Then, an adaptive fixed‐time fault‐tolerant controller is developed for the spacecraft with the actuator faults, such that the fixed‐time convergence of the attitude and angular velocity could be guaranteed, and no prior knowledge on the upper bound of the lumped uncertainties is required anymore in the controller design. Comparative simulations are provided to illustrate the effectiveness and superior performance of the proposed scheme.     

Event‐triggered Guaranteed Cost Consensus of Networked Singular Multi‐agent Systems

The problem of event‐triggered guaranteed cost consensus of discrete‐time singular multi‐agent systems with switching topologies is investigated in this paper. To save the limited network communication bandwidth of multi‐agent systems, a novel event‐triggered networked consensus mechanism is proposed. Based on the graph theory and singular system theory, sufficient conditions of guaranteed‐cost consensus of discrete‐time singular multi‐agent systems are derived and given in the form of the linear matrix inequalities, respectively. A co‐design approach of the multi‐agent consensus gain matrix and the event‐triggered parameters is presented. Furthermore, based on the approach of second class equivalent transformation for singular systems, the cost function is determined, and an explicit expression of consensus functions is presented. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.     

Finite‐Time Optimal Formation Control for Second‐Order Multiagent Systems

This paper studies the problem of finite‐time optimal formation control for second‐order multiagent systems in situations where the formation time and/or the cost function need to be considered. The finite‐time optimal formation control laws are proposed for the cases with or without a leader, respectively. For the case of control being constrained, the time optimal formation problem is considered and an algorithm is designed to derive a feasible solution for the problem concerned. Although the feasible solution may not be optimal, it can provide a lower bound for time for the formation problem with control constraints. Once the given formation time is lower than this bound, the control constraints cannot be ensured. Finally, some numerical examples are given to illustrate the effectiveness of the theoretical results.     

Prescribed performance adaptive neural output control for a class of switched nonstrict‐feedback nonlinear time‐delay systems: State‐dependent switching law approach

This paper investigates the tracking problem for a class of uncertain switched nonlinear delayed systems with nonstrict‐feedback form. To address this problem, by introducing a new common Lyapunov function (CLF), an adaptive neural network dynamic surface control is proposed. The state‐dependent switching rule is designed to orchestrate which subsystem is active at each time instance. In order to compensate unknown delay terms, an appropriate Lyapunov‐Krasovskii functional is considered in the constructing of the CLF. In addition, a novel switched neural network–based observer is constructed to estimate system states through the output signal. To maintain the tracking error performance within a predefined bound, a prescribed performance bound approach is employed. It is proved that by the proposed output‐feedback control, all the signals of the closed‐loop system are bounded under the switching law. Moreover, the transient and steady‐state tracking performance is guaranteed by the prescribed performance bound. Finally, the effectiveness of the proposed method is illustrated by two numerical and practical examples.     

Robust reliable guaranteed cost control of positive interval systems with multiple time delays and actuator failure

This paper addresses the robust reliable guaranteed cost control problem of positive interval systems with multiple time delays and actuator failure for a given quadratic cost function. Through constructing a Lyapunov–Krasovskii functional, a sufficient condition for the existence of robust reliable guaranteed cost controllers is established such that the closed-loop system is positive and asymptotically stable, and the cost function is guaranteed to be no more than a certain upper bound. Based on the linear matrix inequality method, a criterion for the design of robust reliable guaranteed cost controllers is derived which can tolerate all admissible uncertainties as well as actuator failure. Moreover, a convex optimisation problem with linear matrix inequality constraints is formulated to design the optimal robust reliable guaranteed cost controller which minimises the upper bound of the closed-loop system cost. A numerical example is given to show the effectiveness of the proposed methods.     

A robust continuous‐time fixed‐lag smoother for nonlinear uncertain systems

This paper presents a scheme for the design of a robust fixed‐lag smoother for a class of nonlinear uncertain systems. The proposed approach combines a nonlinear robust estimator with a stable fixed‐lag smoother, to improve the estimation error covariance. The robust fixed‐lag smoother is based on the use of integral quadratic constraints and minimax linear quadratic regulator estimation and control theory. The state estimator uses a copy of the system nonlinearity in the estimator and combines an approximate model of the delayed states to produce a smoother signal. Also in this work, a characterization of the delay approximation error is presented, and the corresponding integral quadratic constraint is included in the design, which gives a guaranteed bound on the performance cost function. In order to see the effectiveness of the method, it is applied to a quantum optical phase estimation problem. Results show a significant improvement in the error covariance of the estimator when compared with a robust nonlinear filter. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive sliding‐mode control for Mars entry trajectory tracking with finite‐time convergence

This paper presents a novel adaptive sliding‐mode control (ASMC) method for Mars entry guidance and the finite‐time convergence in the presence of large uncertainties can be guaranteed. With the help of gain adaptive law, the nonoverestimating value of control gains can be achieved, and then, the chattering can be attenuated by the proposed ASMC method. Meanwhile, the extended state observer is introduced to estimate and compensate for uncertainties and the nonoverestimating problem is resolved further. In addition, the proposed method does not require any knowledge on the upper bound of uncertainty, which yields to be used in practical systems. Finally, the numerical simulation results are given to demonstrate the effectiveness of the proposed guidance law.