Adaptive output regulation for cyber-physical systems under time-delay attacks

In this paper,we present an output regulation method for unknown cyber-physical systems(CPSs)under time-delay attacks in both the sensor-to-controller(S-C)channel and the controller-to-actuator(C-A)channel.The proposed approach is designed using control inputs and tracking errors which are accessible data.Reinforcement learning is leveraged to update the control gains in real time using policy or value iterations.A thorough stability analysis is conducted and it is found that the proposed controller can sustain the convergence and asymptotic stability even when two channels are attacked.Finally,comparison results with a simulated CPS verify the effectiveness of the proposed output regulation method.

Adaptive robust simultaneous stabilization of multiple nn-degree-of-freedom robot systems

In this paper,the adaptive robust simultaneous stabilization problem of uncertain multiple n-degree-of-freedom(n-DOF)robot systems is studied using the Hamiltonian function method,and the corresponding adaptive L2 controller is designed.First,we investigate the adaptive simultaneous stabilization problem of uncertain multiple n-DOF robot systems without external disturbance.Namely,the single uncertain n-DOF robot system is transformed into an equivalent Hamiltonian form using the unified partial derivative operator(UP-DO)and potential energy shaping method,and then a high dimensional Hamiltonian system for multiple uncertain robot systems is obtained by applying augmented dimension technology,and a single output feedback controller is designed to ensure the simultaneous stabilization for the higher dimensional Hamiltonian system.On this basis,we further study the adaptive robust simultaneous stabilization control problem for the uncertain multiple n-DOF robot systems with external disturbances,and design an adaptive robust simultaneous stabilization controller.Finally,the simulation results show that the adaptive robust simultaneous stabilization controller designed in this paper is very effective in stabilizing multi-robot systems at the same time.

A blockchain-based transaction system for private data sharing and trading

To address the private data management problems and realize privacy-preserving data sharing,a blockchain-based transaction system named Ecare featuring information transparency,fairness and scalability is proposed.The proposed system formulates multiple private data access control strategies,and realizes data trading and sharing through on-chain transactions,which makes transaction records transparent and immutable.In our system,the private data are encrypted,and the role-based account model ensures that access to the data requires owner’s authorization.Moreover,a new consensus protocol named Proof of Transactions(PoT)proposed by ourselves has been used to improve consensus efficiency.The value of Ecare is not only that it aggregates telemedicine,data transactions,and other features,but also that it translates these actions into transaction events stored in the blockchain,making them transparent and immutable to all participants.The proposed system can be extended to more general big data privacy protection and data transaction scenarios.

Distributed solving Sylvester equations with fractional order dynamics

This paper addresses distributed computation Sylvester equations of the form AX+XB=C with fractional order dynamics.By partitioning parameter matrices A,B and C,we transfer the problem of distributed solving Sylvester equations as two distributed optimization models and design two fractional order continuous-time algorithms,which have more design freedom and have potential to obtain better convergence performance than that of existing first order algorithms.Then,rewriting distributed algorithms as corresponding frequency distributed models,we design Lyapunov functions and prove that proposed algorithms asymptotically converge to an exact or least squares solution.Finally,we validate the effectiveness of proposed algorithms by providing a numerical example.

Limit behaviors of extended Kalman filter as a parameter estimator for a sinusoidal signal

In this note, the basic limit behaviors of the solution to Riccati equation in the extended Kalman filter as a parameter estimator for a sinusoidal signal are analytically investigated by using lira sup and lim inf in advanced calculus. We show that if the covariance matrix has a limit, then it must be a zero matrix.

Call for papers The 36th Chinese Control Conference （CCC201 7）

The 36th Chinese Control Conference is organized by the Technical Committee on Control Theory （TCCT） of Chinese Association of Automation （CAA）, and locally organized by Dalian University of Technology （DUT）.

Control of a flexible rotor active magnetic bearing test rig: a characteristic model based all-coefficient adaptive control approach

Active magnetic bearings （AMBs） have found a wide range of applications in high-speed rotating machinery industry. The instability and nonlinearity of AMBs make controller designs difficult, and when AMBs are coupled with a flexible rotor, the resulting complex dynamics make the problems of stabilization and disturbance rejection, which are critical for a stable and smooth operation of the rotor AMB system, even more difficult. Proportional-integral-derivative （PID） control dominates the current AMB applications in the field. Even though PID controllers are easy to implement, there are critical performance limitations associated with them that prevent the more advanced applications of AMBs, which usually require stronger robustness and performance offered by modern control methods such as H-infinity control and if-synthesis. However, these advanced control designs rely heavily on the relatively accurate plant models and uncertainty characterizations, which are sometimes difficult to obtain. In this paper, we explore and report on the use of the characteristic model based all-coefficient adaptive control method to stabilize a flexible rotor AMB test rig. In spite of the simple structure of such a characteristic model based all-coefficient adaptive controller, both simulation and experimental results show its strong performance.

New approaches to relaxed stabilization conditions and H-infinity control designs for T-S fuzzy systems

This paper focuses on the problem of fuzzy control for a class of continuous-time T-S fuzzy systems. New methods of stabilization design and H-infinity control are derived based on a relaxed approach in which both fuzzy Lyapunov functions and staircase membership functions are used. Through the staircase membership functions approx- imating the continuous membership functions of the given fuzzy model, the membership functions can be brought into the design conditions of fuzzy systems, thereby significantly reducing the conservativeness in the recent fuzzy controller design methods. Unlike some previous fuzzy Lyapunov function approaches reported in the literatures, the proposed design techniques of stabilization and H-infinity control do not depend on the time-derivative of the membership functions that may be pointed out as the main source of conservatism when considering fuzzy Lyapunov functions analysis. Moreover, conditions for the solvability of the controller design given here are written in the form of linear matrix inequalities, but not bilinear matrix inequalities, which are easier to be solved by convex optimization techniques. Simulation examples are given to demonstrate the validity and applicability of the proposed approaches.

Optimal linear estimators for systems with random measurement delays

This paper is concerned with the optimal linear estimation problem for linear discrete-time stochastic systems with random measurement delays. A new model that describes the random delays is constructed where possible the largest delay is bounded. Based on this new model, the optimal linear estimators including filter, predictor and smoother are developed via an innovation analysis approach. The estimators are recursively computed in terms of the solutions of a Riccati difference equation and a Lyapunov difference equation. The steady-state estimators are also investigated. A sufficient condition for the convergence of the optimal linear estimators is given. A simulation example shows the effectiveness of the proposed algorithms.

New versions of Barbalat's lemma with applications

This note presents a set of new versions of Barbalat＇s lemma combining with positive （negative） definite functions.Based on these results,a set of new formulations of Lyapunov-like lemma are established.A simple example shows the usefulness of our results.

Stability and boundedness in terms of two measures for nonlinear impulsive control systems

In this paper we study stability and boundedness in terms of two measures for impulsive control systems. By using variational Lyapunov method, a new variational comparison principle and some criteria on stability and boundedness are obtained. An example is presented to illustrate the efficiency of proposed result.

Information for Authors

The Journal of Control Theory and Applications （JCTA） publishes high-quality papers on the theory, design, and applications in the systems and control field. This journal is published quarterly. Three types of contribution s are regularly considered：

Synchronization of general discrete Lur'e systems

This paper studies a master-slave type of synchronization systems for a general form of two discrete Lur＇e systems. Some simple necessary and/or sufficient conditions for synchronization are derived. They are basically algebraic conditions, and are convement to be applied in engineering applications.

Neural model-based adaptive control for systems with unknown Preisach-type hysteresis

An adaptive control scheme is presented for systems with unknown hysteresis. In order to handle the case where the hysteresis output is unmeasurale, a novel model is firstly developed to describe the characteristic of hysteresis. This model is motivated by Preisach model but implemented by using neural networks ( NN) . The main advantage is that it is easily used for controller design. Then, the adaptive controller based on the proposed model is presented for a class of SISO nonlinear systems preceded by unknown hysteresis, which is estimated by the proposed model. The laws for model updating and the control laws for the neural adaptive controller are derived from Lyapunov stability theorem, therefore the semiglobal stability of the closed-loop system is guaranteed. At last, the simulation results are illustrated.

Time-shared channel identification for adaptive noise cancellation in breath sound extraction

Noise artifacts are one of the key obstacles in applying continuous monitoring and computer-assisted analysis of lung sounds. Traditional adaptive noise cancellation (ANC) methodologies work reasonably well when signal and noise are stationary and independent. Clinical lung sound auscultation encounters an acoustic environment in which breath sounds are not stationary and often correlate with noise. Consequendy, capability of ANC becomes significantly compromised. This paper introduces a new methodology for extracting authentic lung sounds from noise-corrupted measurements. Unlike traditional noise cancellation methods that rely on either frequency band separation or signal/noise independence to achieve noise reduction, this methodology combines the traditional noise canceling methods with the unique feature of time-split stages in breathing sounds. By employing a multi-sensor system, the method first employs a high-pass filter to eliminate the off-band noise, and then performs time-shared blind identification and noise cancellation with recursion from breathing cycle to cycle. Since no frequency separation or signal/noise independence is required, this method potentially has a robust and reliable capability of noise reduction, complementing the traditional methods.

Distributed adaptive Kalman filter based on variational Bayesian technique

In this paper, distributed Kalman filter design is studied for linear dynamics with unknown measurement noise variance, which modeled by Wishart distribution. To solve the problem in a multi-agent network, a distributed adaptive Kalman filter is proposed with the help of variational Bayesian, where the posterior distribution of joint state and noise variance is approximated by a free-form distribution. The con vergence of the proposed algorithm is proved in two main steps: n oise statistics is estimated, where each age nt only use its local information in variational Bayesian expectation (VB-E) step, and state is estimated by a consensus algorithm in variational Bayesian maximum (VB-M) step. Finally, a distributed target tracking problem is investigated with simulations for illustration.

Feedback stabilization of N-dimensional stochastic quantum systems based on bang-bang control

For an N-dimensional quantum system under the influence of continuous measurement, this paper presents a switching control scheme where the control law is of bang-bang type and achieves asymptotic preparation of an arbitrarily given eigenstate of a non-degenerate and degenerate measurement operator, respectively. In the switching control strategy, we divide the state space into two parts： a set containing a target state, and its complementary set. By analyzing the stability of the stochastic system model under consideration, we design a constant control law and give some conditions that the control Hamiltonian satisfies so that the system trajectories in the complementary set converge to the set which contains the target state. Further, for the case of a non-degenerate measurement operator, we show that the system trajectories in the set containing the target state will automatically converge to the target state via quantum continuous measurement theory; while for the case of a degenerate measurement operator, the corresponding system trajectories will also converge to the target state via the construction of the control Hamiltonians. The convergence of the whole closed-loop systems under the cases of a non-degenerate and a degenerate measurement operator is strictly proved. The effectiveness of the proposed switching control scheme is verified by the simulation experiments on a finite-dimensional angular momentum system and a two-qubit system.

A survey on the security of cyber-physical systems

Cyber-physical systems （CPSs） are integrations of computation, communication, control and physical processes. Typical examples where CPSs are deployed include smart grids, civil infrastructure, medical devices and manufacturing. Security is one of the most important issues that should be investigated in CPSs and hence has received much attention in recent years. This paper surveys recent results in this area and mainly focusses on three important categories： attack detection, attack design and secure estimation and control. We also discuss several future research directions including risk assessment, modeling of attacks and attacks design, counter-attack strategy and testbed and validation.

Editorial Special issue on disturbance rejection： a snapshot, a necessity, and a beginning

A fundamental responsibility of a scientist is to continue to question how the problems are framed and what presumptions are made. This is particularly true in the field of automatic control, which has been pre-occupied with the study of stability and optimality, premised on the accurate mathematical description of the physical processes. Central to the engineering practice, however, is the problem of internal and external disturbances, as articulated brilliantly by Prof. H. S. Tsien some 60 years ago. The history of automatic control has been, therefore, the history of two distinct conceptualizations： of stability and optimality on the one hand and of disturbance rejection on the other. This special issue in Control Theory and Technology is a timely snapshot of some current work in the latter. With only seven papers, it is obviously a limited sample of the questions being asked and the progress made. Nonetheless, it points to the necessity and urgency of such a study, which has become increasingly active in recent years.

Call for papers Special issue on Modeling and control technologies for civil,energy,and power systems

The control of civil, energy, and power systems presents significant new challenges for modeling and control theory. The purpose of this special issue is to provide a forum for researchers and practical engineers to discuss the recent advances in modeling and control technology development for civil, energy, and power systems. Prospective authors are invited to submit their original contributions with the focus on theory or applications of modeling, control and decision. Topics of interest include modeling and control of, but are not limited to, the following：