Asian Journal of Control最新文献

In this paper, we discuss a new approach to balancing (known as dynamic–quadratic balancing) and model reduction for affine nonlinear system. We give a fresh look to balancing in terms of the dynamics of the system, rather than simply a structural property. With this perspective, we also develop a new approach to obtaining the balancing transformation in one step, instead of a three-step process as proposed in earlier methods. Further, we explore the relationship between quadratic balancing and input–output stability. In addition, we also develop a computational approach for obtaining the balancing transformation by solving a coupled system of PDEs or inequalities (Lyapunov/Hamilton–Jacobi type). After that, model reduction can be carried out in the conventional way using Hankel singular-value functions or using a new criterion. Finally, we present some examples to clarify the results.

This paper investigates the robust stability and stabilization problems of continuous-discrete fractional-order two-dimensional Fornasini–Marchesini second model with interval uncertainties. Firstly, for the nominal model with fractional-order $��\alpha �\in �\left(�\mathrm{0,2}�\right)�$, the unified LMI-based stability conditions are presented by general description of stable root-clustering sets. Secondly, these stability conditions are transformed to be more tractable for stabilization, and the LMI/BMI-based stabilization conditions are established via state feedback controllers. Meanwhile, one algorithm is proposed to solve the BMI-based conditions. Thirdly, facing interval uncertainties in this model, the LMI-based robust stability conditions and LMI/BMI-based robust stabilization conditions are established. Lastly, two examples are given to show the validity of our robust stability and stabilization results.

In this paper, the distributed moving horizon fusion estimation of uncertain systems with constraints of system noise and state variables is studied. Firstly, relying on the basic idea of consensus algorithm, the cost function in the performance index is reconstructed by weighted fusion of the state prediction values. Secondly, considering the performance index with uncertain parameters, the min-max optimization problem of the algorithm is transformed into the least squares optimization problem based on 2-norm regularization method. Thirdly, the scalar-weighted linear minimum variance fusion estimation strategy is used to realize the weighted fusion of local state estimation values. Then, on the premise of minimum network connectivity and collective observability, the stability of the proposed algorithm is studied, and the sufficient conditions for the expected convergence of the fused estimation error norm square are given. Finally, the effectiveness of the algorithm is verified by numerical simulation.

This paper is considered with the asymptotic stabilization of coupled delayed nonlinear time fractional reaction diffusion systems (FRDSs) governed by fractional parabolic partial differential equations (PDEs) with space-dependent coefficients under sampled-data in space control. It is assumed that state measurements can be averaged measurements (AMs) or point measurements (PMs), and a finite number of sensing and actuation devices are located in a spaced manner along the spatial domain of the interest. With the proposed sampled-data in space controller, the closed-loop $��{�H�}^{�1�}�$ stability is obtained. Tuning rules of system parameters and control parameters are derived using the fractional Halanay's inequality and the fractional Lyapunov method. Subsequently, the dual problem of observer design is formulated. Fractional examples are used to valid the theoretical result. Discussions on the extension of sampled-data boundary feedback stabilization are provided finally.

In this paper, a novel dynamic event-triggered control protocol for leader-following problems of generic linear multi-agent systems is proposed. Compared with the existing static event-triggered strategy, the developed event-triggered approach significantly reduces the utilization of communication resources while guaranteeing asymptotic consensus, and the interevent time is adjustable. Under this event scheduling mechanism, a synthesis approach combining controller and observer design is presented. The observer-based control and event-triggered rules are distributed, which only require local information of each agent to implement. The proposed methods incorporate model-based estimation and auxiliary dynamic variables with a clock-like behavior to prolong the interevent time as long as possible. The sufficient conditions for leader-following consensus are established using linear matrix inequalities (LMIs) formulation to facilitate numerical computation. Comparative simulations in different scenarios demonstrate the validity of the proposed theoretical results.

We investigate the stabilization problem of positive Markov jump linear systems by optimizing their transition probability rates. By using the convex property of posynomials and the standard mathematical programming that deals with the difference in convex functions, we show that transition probability rate synthesis problems can be solved via difference-of-convex (DC) programming. A numerical example is used to illustrate the effectiveness of our results.

This paper investigates a challenging heading control problem for a flexible paraglider recovery system with input saturation. A fixed-time observer-based control approach is presented. In this approach, a fixed-time disturbance observer is preliminarily designed to estimate the aerodynamic uncertainties and the complex coupling of the subsystems. A fixed-time auxiliary system is then proposed to compensate for input saturation impact. With the application of the estimated and compensation values, a novel heading tracking controller is synthesized with compensated disturbance. The key feature of the scheme is that it is not only fixed time stable regardless of any initial state, but also it prevents control performance degradation due to input saturation and various disturbances. Simulation results verify the effectiveness of the proposed method.

In this paper, we uncover a new connection between standard proportional-integral (PI), proportional-integral-derivative (PID) controllers and active disturbance rejection control (ADRC), from which we establish formal conditions of equivalence between the two control schemes. Using the equivalence, we devise a step-by-step procedure of transitioning from PI/PID to error-based ADRC. We also show how to go from one degree-of-freedom (1DOF) to two degree-of-freedom (2DOF) ADRC while retaining a standard 2DOF PI/PID structure. Both procedures facilitate expressing error-based ADRC schemes as standard industrial 1DOF and 2DOF controllers. This allows the designed controller to have the desired characteristic of ADRC (i.e., strong robustness against internal and external uncertainties) while still being expressed in a form that is familiar to industrial practitioners, where PI/PID structures are still the workhorse of modern control systems. The paper's results ensure backward compatibility of future ADRC-based solutions and foster the adoption of active disturbance rejection-based methods in industrial practice as a viable alternative to standard controllers. To further support the findings, a set of tests is conducted in time and frequency domain.

This paper researches the adaptive bipartite output containment control of heterogeneous multi-agent systems (HMASs) against false data injection (FDI) attacks. The malicious adversaries could inject attacks on the actuator to maximize damage to the HMASs, which in turn causes the compromised followers to be unable to track the output states of the leaders. To address this issue, a resilient layer is introduced that prevents attack signals from affecting the states. Moreover, an adaptive compensator is ingeniously devised to counteract these attacks, thereby ensuring that both cooperative and antagonistic agents adhere to distinct convex hulls. Leveraging the output regulation approach, conducting Lyapunov stability analysis, and drawing upon other pertinent methodologies, we have systematically constructed a robust framework for the realization of bipartite output containment control. Ultimately, the validity of the analytical findings is confirmed through a series of rigorous numerical simulations.