This article addresses the problem of dynamic event-triggered asynchronous output feedback controller design for discrete-time switched systems under deception attacks. To conserve communication resources and restrict asynchronous time, a dynamic event-triggered mechanism is established which permits the system to switch many times in the trigger interval. Then, stability criteria for the underlying system despite the impact of deception attacks are obtained via the Lyapunov function and average dwell time method. Meanwhile, a co-design scheme for dynamic output feedback gains and dynamic event-triggered parameters are provided. Finally, two simulations are used to demonstrate the effectiveness of the approach.
This paper addresses the problem of adaptive robust safety-critical control (ARSCC) for switched systems, where the safety of subsystems is not necessary. A novel ARSCC framework and an executable algorithm are presented to solve the ARSCC problem by finding a switching signal and controllers of subsystems. To estimate uncertainties, a novel switched piecewise-constant adaptive law is presented, which guarantees a pre-computable estimation error boundary. A single barrier function (SBF) method is proposed to ensure safety of switched systems with uncertainties, where the safety of subsystems is satisfied only in some subregion of a given safe set, instead of the whole safe set. Based on the SBF method, a novel state-dependent switching law possessing different dwell times for different subsystems, is established to orchestrate the switching among potentially unsafe subsystems. As a special case of the SBF method, a common barrier function method is presented to achieve safety of switched systems with uncertainties under switching signals with given dwell times. In addition, some sufficient conditions are derived to obtain safety and asymptotic stability for switched systems with uncertainties by combining SBF and single Lyapunov function. Finally, a switched RLC circuit system is given to illustrate the effectiveness of the theoretical results.
This paper addresses the strong consensus problem of convex second-order discrete-time multi-agent systems (MASs) with time-varying topologies. The convex second-order discrete-time MAS model is derived from the Langevin equation and therefore has a certain physical significance. The strong consensus here means that all the first- and second-order states converge to an identical value. Some fully distributed control protocols are designed with time-varying weights randomly chosen from an arbitrary finite set. These protocols are applicable to several cases where changing topologies may be directed or undirected, and connected or disconnected. As a special case, the condition for convex second-order MASs with fixed topologies to achieve the strong consensus is presented. Finally, two simulation examples illustrate the proposed results.
An innovative technique for developing fuzzy preview tracking control nonlinear systems using Takagi-Sugeno (T-S) fuzzy models is discussed. The design considers robustness against state time-changing latency, input saturation, and reference tracking. To achieve this, the T-S fuzzy system was combined with time-changing latency and input saturation to create an augmented error system, transforming the original fuzzy preview tracking control issue into a stability issue for the augmented error systems. Next, a new fuzzy preview tracking controller was developed by considering the T-S fuzzy systems' states or outputs, a distinct integrator, and a previewed reference signal to solve the tracking control issue. For the augmented error system's asymptotic stability, new adequate conditions were derived by employing the fuzzy Lyapunov function, small gain theory, and linear matrix inequality (LMI) method. Finally, the proposed method's effectiveness was demonstrated using two numerical examples.
This paper investigates the adaptive fuzzy backstepping control problem for uncertain discrete-time nonlinear systems with mismatched disturbances. A novel adaptive fuzzy command filtered backstepping approach is proposed, which can overcome the noncausal problem by using the command filter. The filter errors generated by filter are removed by constructing error compensation mechanism. The fuzzy logic systems are used to approximate the uncertain nonlinear dynamics, and the unknown mismatched disturbances are actively attenuated by using adaptive control technique. Based on the proposed new weighed Lyapunov functions, all the signals in the close-loop system are proved to be uniformly ultimately bounded. The viability of proposed method is demonstrated by simulation results.
This paper addresses the guaranteed performance control problem for a class of singular switched positive systems, where the switching signal is subject to a state-dependent process. Firstly, the causality, regularity, positivity, and asymptotical stability of the considered systems are discussed. In order to prevent the occurrence of data collisions and reduce the consumption of communication resources, the event-triggered (E-T) mechanism is applied. This is one of the initial attempts to introduce the E-T scheme for such special systems. Besides, an asynchronous nonfragile controller under the E-T scheduling scheme is designed to make certain that the resulting closed-loop systems are causal, regular, positive, asymptotically stable, and have a guaranteed performance value . Through the application of the co-positive Lyapunov function method and the min-projection strategy, the corresponding sufficient conditions are given in the form of linear programming (LP). Finally, the effectiveness of the controller proposed in this paper is verified via two simulation examples.
It is very difficult to control the distributed parameter system (DPS) for consistent spatial performance. In this paper, a dual scale spatio-temporal control is designed for the DPS to achieve a consistent performance across the entire workspace under unknown exogenous disturbances. First, the generalized “spatial observer” should be designed under spectral decomposition/synthesis, to act as the nominal model of the DPS, through which the spatial mismatch between the model and the process could be estimated. Then a distributed disturbance compensator can be constructed to suppress all the undesirable spatial disturbance through the inner loop, and the compensated system will become closer to the nominal model and easier to control. Third, a dual controller will be designed in the outer loop for the final consistent spatial performance. Since the spatial performance is mainly affected by the dominant dynamics on the slow scale, a convex optimization algorithm can be effectively established in terms of nonlinear matrix inequalities for the dual controller. In this way, the nonlinear optimization problem is solved by converting it into the problem of a linear matrix inequalities with constraints. Besides, the spatio-temporal state variable of the controlled plant is demonstrated to converge in Hilbert space. The feasibility and effectiveness of the proposed control method are verified by temperature control of a catalytic rod, a benchmark in chemical reactors.
This article investigates the asynchronous control for a class of nonlinear switched stochastic delayed systems. In response to this issue, the weighted mode-dependent average dwell time is first applied to switched stochastic systems as a more general switching signal. In addition, the asynchronous phenomenon is considered to address the mismatch in practical applications, where “mismatch” means the switching of the controllers has a delay to the switching of system modes. Then by selecting new multiple Lyapunov–Krasovskii functionals, sufficient conditions for mean-square exponential stability and an performance are derived. Finally, numerical examples are provided to illustrate the effectiveness of the proposed methods.
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