Decentralized output feedback control for nonlinear similar large-scale composite systems with unmatched uncertainties

This paper studies the problem of global decentralized control by applying time-varying output feedback for large-scale uncertain systems whose subsystems are interconnected not only by their outputs but also by their unmeasurable states. We show that under a linear growth condition, there is a decentralized output feedback controller rendering the closed-loop systems globally exponentially stable. This is accomplished by extending and output feedback domination design which requires little information about the nonlinear systems. Furthermore, we apply our results to a multi-vehicle system to demonstrate the use of our time-varying output feedback controller.

In this article, finite-time control is investigated for multiple time-delayed large-scale nonlinear systems against state and input constraints. There are multiple time-varying delays, intermittent actuator faults, and intermittent sensor faults in this model. Takagi–Sugeno fuzzy model is used to describe the nonlinear system. There are few tries to studying finite-time control for large-scale nonlinear systems. First, a dynamic output feedback controller is designed in this article to make the system finite-time bounded. Then, an augmented closed-loop model is constructed. Sufficient conditions of finite-time control are given by the fuzzy Lyapunov function. Finally, the feasibility of the approach is verified by two simulation examples.

This paper proposes a novel adaptive synchronization approach for a class of nonlinear large-scale systems via T-S fuzzy model. It is known that the practical large-scale systems are very complicated with nonlinear coupling strength between every two subsystems, thus the classical linear control methods are invalid for them. To overcome this deficiency, we employ the T-S fuzzy model in this paper. Firstly, the local linearization approach is utilized to preprocess the nonlinear large-scale systems, and then, according to the universal approximation property of TS fuzzy model, a new system model is established. Secondly, the fuzzy adaptive synchronization controllers are designed by using Parallel Distributed Compensation technique and the corresponding stability analysis is presented through Lyapunov technique. In addition, a new criterion, under which the proposed control scheme can be transformed into pinning control and save unnecessary costs, is also given. Finally, a numerical simulation example is presented to demonstrate the effectiveness of our proposed approach.

In this paper, asymptotic stabilization for a class of nonlinear large-scale systems with unmatched uncertainties is investigated. Two types of robust control algorithms are proposed to stabilize the uncertain nonlinear large-scale systems asymptotically provided that the nominal systems are asymptotically stable and the unmatched uncertainties are equivalently matched. The decentralized control utilizes the local state of each subsystems as the feedback information. The two-level control uses the local state as well as the states of the state of the connecting subsystems. An example is used to illustrate the proposed control method.

Describes the similarity between two nonlinear control systems, shown in a large number of physical systems of interest in many engineering applications. By utilising similar information, robust controllers for large-scale nonlinear similar composite systems with uncertain parameters are proposed. The results obtained show that the similar structure of composite systems possesses a holographic property and can simplify the analysis and design of nonlinear systems.

Delay-dependent robust and reliable [formula omitted] fuzzy hyperbolic decentralized control for uncertain nonlinear interconnected systems

A new approach using graph-theory to determine the controllability and observability of large scale nonlinear dynamic thermal systems is presented. The novelty of this method is in adapting graph theory for a nonlinear class and establishing graphic conditions that describe the necessary and sufficient conditions for a class of nonlinear systems to be controllable and observable which is equivalent to the analytical method of Lie algebra rank condition. Graph theory of directed graph (digraph) is utilized to model the system and its adaptation to nonlinear problems is defined. The necessary and sufficient conditions for controllability are investigated through the structural property of a digraph called connectability. In comparison to the Lie Algebra, this approach has proven to be easier, from a computational point of view, thus it is found to be useful when dealing with large scale systems. This paper presents the problem statement, properties of structured system, and analytical method of Lie algebra rank condition for controllability and observability of bilinear systems. The main results of graphical approach which describe the necessary and sufficient conditions for controllability of nonlinear systems are presented and applied to the problem of a coupled two heat exchangers, connected in an arbitrary fashion.

In this paper, the problem of delay-dependent decentralized control for a class of nonlinear large-scale interconnected systems with similar structure is investigated, where the linear state vectors, the nonlinear state vectors and the nonlinear interconnections involve time delays. The new similar structure is presented via memory feedback. Based on which, by exploiting the structure of interconnected systems, the new integral inequalities, constrained Lyapunov equations and LMI method, a decentralized memory derivative feedback control strategy is proposed to stabilize the resulting interconnected systems uniformly asymptotically, in addition, the stability domain is estimated. Finally, simulation results show the effectiveness of the proposed approach.

This paper considers the global optimal control for nonlinear interconnected large-scale systems with respect to linear quadratic functional. A successive approximation procedure is proposed to design the feedforward feedback nearly optimal control law. By introducing the Successive Approximation Approach of the nonlinear differential equation theory, a nonhomogeneous linear two-point boundary value problem sequence is constructed to approximate the nonlinear large-scale two-point boundary value problem, which is the necessary condition of the nonlinear control problem. By iteratively solving this nonhomogeneous linear approximating sequence, a global nearly optimal control law that composed of a linear closed-loop feedback compensatory term and an open-loop feedforward compensatory term is designed. An algorithm is presented to design certain qualified nearly optimal control law by truncating an infinite iteration result. An illustrative example shows the validity of the algorithm.

In this paper, we consider decentralized adaptive output-feedback control problem for a class of large-scale nonlinear systems, in which the nonlinear actions within subsystems and nonlinear interactions between subsystems contain unknown time delays, and need not satisfy the matching condition. A memoryless decentralized adaptive output-feedback controller is proposed, and global stability results of the closed-loop system are proved.

Adaptive decentralized NN control of large-scale stochastic nonlinear time-delay systems with unknown dead-zone inputs

After pointing out the special characteristics of existing econometric models which form the basis of the application of optimal control techniques for macroeconomic policy analysis and formulation, this paper surveys the use of econometric models for the projection of the economic consequences of alternative policies and the formulation of optimal policies. It presents both the theory and the computational aspects of a particular approach of applying feedback control to study policy options using large-scale nonlinear systems of simultaneous econometric equations. It then illustrates this approach by solving an optimal control problem using the Michigan Quarterly Econometric Model Some topics of further research are suggested in the conclusion.

This paper solves the finite-time decentralized control problem for uncertain nonlinear large-scale systems in nonstrict-feedback form. The considered controlled plants are different from the previous results of finite-time control systems, which are the nonstrict-feedback large-scale systems with the unknown functions consisting of all states, interactions, and immeasurable states. Fuzzy logic systems and a filter-based state observer are utilized to model uncertain systems and deal with the immeasurable states, respectively. By combining the backstepping recursive design with Lyapunov function theory, a finite-time adaptive fuzzy decentralized control approach is raised. It is testified that the developed control strategy can guarantee that the closed-loop signals are bounded, and the outputs of systems have satisfactory tracking performance in a finite time. A quadruple-tank process system is given to testify the effectiveness and applicability of the proposed approach.

The optimal output tracking control problem for nonlinear large-scale dynamic systems is considered. A series-based approximate approach for designing the optimal controller is proposed with respect to quadratic performance indexes. By using the approach, the high order, coupling, nonlinear two-point boundary value problem is transformed into a sequence of linear decoupling two-point boundary value problems. By intercepting the frontal finite terms of the solution series, we obtained a suboptimal tracking control law. A simulation example illustrates the efficiency of the optimal output tracking control law designed.

In this paper, a novel cooperative constrained distributed model predictive control algorithm is proposed to control the nonlinear interconnected constrained large-scale systems. In this algorithm, a novel reduced-order cooperative optimisation approach is proposed which is its main contribution that reconstructs and improves the global cost function of any local controller. In proposed algorithm, each local controller computes its optimal control by minimising the corresponding global cost function which is a combination of its own and its neighbouring subsystems’ cost functions. The sufficient conditions are derived to guarantee the recursive feasibility and closed-loop stability specifications to ensure the convergence of the overall states into the positive region which is the neighbourhood of origin. The performance of the proposed algorithm is illustrated via simulation results of a nonlinear large-scale cart-spring-damper system.