Asian Journal of Control最新文献

This paper studies the optimal tracking performance (OTP) of multiple-input multiple-output (MIMO) discrete communication constrained systems (CCSs) with fading channel and quantization constraints. An equivalent average channel is used to replace the fading channel with colored noise, and the gain of the output ports of the two channels is consistent in the first and second moments. Combined with spectral decomposition, co-prime decomposition, partial fractional decomposition and other methods, the quantitative explicit expression of OTP is eventually derived. The result shows that the OTP is related to nonminimum phase (NMP) zeros and unstable poles and their directions of controlled plant, and is also affected by quantization error and colored noise. At last, a numerical example is utilized to verify the theory.

Economic dispatch constitutes an important element within the hierarchical control framework of smart grids. Its effective implementation is imperative for cost reduction in generation, enhancement of operational efficiency, and power systems stability. This paper tackles the distributed economic dispatch problem in smart grids with transmission line losses. First, the economic dispatch problem is transformed into its Lagrange dual problem using convex optimization theory, accompanied by a description of the strategy for addressing inequality constraints. Then, a fully distributed optimization algorithm is developed under free initial state through the fusion of nonsmooth analysis and the primal–dual method. Furthermore, based on this algorithm, a modified algorithm with lower communication overhead is presented. Finally, software simulations and hardware-in-the-loop tests are performed to verify the developed scheme.

This paper investigates discrete-time high-order fully actuated (DT-HOFA) robust stabilization control for a type of combined spacecraft simulator (CSS) subject to nonlinear uncertainties. First, a discrete-time second-order fully actuated system (FAS) model is developed for the CSS system and generalized to a general DT-HOFA system (HOFAS) with nonlinear uncertainty, after which the robust control objective is proposed. Then, based on a linear matrix inequality condition, a robust stabilizing controller for the uncertain DT-HOFAS is designed under certain nonlinear uncertainties, which produces a closed-loop system with arbitrarily assignable eigenstructure. The assignable nature of the closed-loop system is further utilized to improve the system performance by solving a multi-objective optimization problem. Finally, the proposed approach is applied successfully to solve the robust stabilization control task of CSS with nonlinear uncertainties, and simulation and experimental results verify its convenience and effectiveness for practical use.

This paper focuses on the consensus problem for heterogeneous multi-agent systems (HMASs) consisting of second-order linear agents and nonlinear Euler–Lagrange (EL) agents. Firstly, the HMASs consensus control protocols are designed in the cases of leaderless and leader-following, respectively. Among them, the research of these two parts is based on the undirected communication topology. Then, through the mathematical knowledge such as graph theory and Lasalle's invariance principle, the sufficient conditions of consensus are given, and the stability of the controller is further proved. At last, the validity of the above theory is proved by simulation results.

The air rudder electromechanical servo system plays a crucial role in ensuring the safe and efficient operation of the aircraft. However, the immeasurable command output and the mismatched channel between input and unknown disturbance bring great challenges to its controller design. To tackle this issue, this study proposes a disturbance compensation-based feedback linearization servo control strategy. This approach uses a radial basis function neural network-based nonlinear observer to estimate the immeasurable command output and disturbance. Subsequently, a feedback linearization control algorithm is employed using these estimations to achieve disturbance compensation for the air rudder electromechanical system. Following the Lyapunov stability theorem, it is proved that the stability of the electromechanical servo system under the designed control algorithm can be guaranteed. At last, extensive simulation results are provided to demonstrate the effectiveness of the proposed control approach.

This paper is devoted to the event-triggered fault-tolerant bounded consensus tracking control for switched multi-agent systems (MASs) with full-state constraints and actuator faults. By using backstepping technology and fuzzy logic systems (FLSs), an event-triggered fault-tolerant control (FTC) scheme is constructed for switched MASs for the first time, which compensates the impact of actuator faults on the system and significantly reduces the updating frequency of controllers. The asynchronous switching error compensation functions are introduced into the designed controller and triggering mechanism, which solves the asynchronous switching problem prompted by the interaction of triggering and switching together effectively. In the meantime, the system states are restricted within the given sets under the barrier Lyapunov functions (BLFs). All the closed-loop signals are bounded and the bounded consensus tracking control is realized with average dwell time (ADT). Finally, an example of chemical reactors is established for demonstrating the effectiveness of the developed scheme.

The purpose of this paper is to provide the linearization technique to solve the multidimensional control optimization problem (MCOP) involving first-order partial differential equation (PDEs) constraints. Firstly, we use the modified objective function approach for simplifying the aforesaid extremum problem (MCOP) and show that the solution sets of the original control optimization problem and its modified control optimization problem (MCOP)$��{}_{�\Omega �}�$ are equivalent under convexity assumptions. Further, we use the absolute value exact penalty function method to transform (MCOP)$��{}_{�\Omega �}�$ into a penalized control problem (MCOP)$��{}_{�\Omega �\varrho �}�$. Then, we establish the equivalence between a minimizer of the modified penalized optimization problem (MCOP)$��{}_{�\Omega �\varrho �}�$ and a saddle point of the Lagrangian defined for the modified optimization problem (MCOP)$��{}_{�\Omega �}�$ under appropriate convexity hypotheses. Moreover, the results established in the paper are illustrated by some examples of MCOPs involving first-order PDEs constraints.

This paper deals with the asynchronous passive control based on event-triggered scheme for Markov jump systems with complex probabilities. A hidden Markov model with uncertain and unknown conditional probabilities is presented to describe the asynchronization. The complex probabilities consider that both transition probability matrix and conditional probability matrix in hidden Markov model contain uncertain and unknown elements simultaneously, with the former governing the jump of system mode and the latter representing the asynchronous relation between the system mode and the controller mode. Asynchronous control strategies based on hidden Markov model with complex probabilities are proposed under event-triggered scheme. Furthermore, sufficient conditions are established to guarantee the stochastic passivity, under which the mode-dependent controller gains and weighting matrices in the event-triggered scheme are co-designed. Theoretical results are finally verified via an example.