Shock is ubiquitous in life and often has a negative impact on human activities. Recently, researchers have tried various controllable materials and structures in the field of shock isolation, achieving active and semi-active control, especially various Magneto-Rheological (MR) dampers. However, there are problems such as the accuracy of the simulation model is not high and the traditional control

In this study, a novel fault estimation and fault tolerant control (FTC) scheme is proposed for a class of nonlinear spacecraft formation flying systems in actuator fault and saturation case, in which the directed communication topology with leader spacecraft as the root. The decentralized unknown input observer is designed to estimate the unknown actuator fault factors, which affect the performance

We propose a formulation of the finite horizon optimal control problem (FHOCP) based on inverse dynamics for general open-chain rigid-body systems, which reduces the computational cost from the conventional formulation based on forward dynamics. We regard the generalized acceleration as a decision variable and inverse dynamics as an equality constraint. To treat under-actuated systems with inverse

A novel three-dimensional modified true proportional navigation (MTPN) guidance and its inverse optimal form are proposed for the interception of the nonmaneuvering and maneuvering targets, and the nonlinear dynamic characteristics of pursuit situations and target maneuvers are taken into full account. The proposed approach is feasible without knowing any prior information or estimate of the target

In this work, we develop and analyze a mathematical model for the dynamics of COVID-19 with re-infection in order to assess the impact of prior comorbidity (specifically, diabetes mellitus) on COVID-19 complications. The model is simulated using data relevant to the dynamics of the diseases in Lagos, Nigeria, making predictions for the attainment of peak periods in the presence or absence of comorbidity

In this paper, a subdivision strategy for the adjoining cell mapping method to solve the global optimal control problems for multi-input-multi-output systems is proposed. The subdivision strategy constructs the discrete optimal control table first by a rough discretization of the state space, which can identify uncontrollable regions. Then the optimal feedback control from the selected initial state

The performance of state estimation of discrete-time Takagi–Sugeno systems is enhanced by proposing a featured multiinstant united switch-type observer. The novelty of the proposed observer lies in both the definition and application of a set of switching modes. Since different time-variant free matrices can be for the first time introduced in accordance with each switching mode, both the current time

This article seeks to develop the dynamic model of a mobile robot for controlling purposes while the effects of uncertainties and longitudinal and lateral slip are assumed. The rise in the number of state variables and considering the effects of nonlinear parameters due to slip modeling can complicate the control procedure of wheeled mobile manipulators. In addition, the existence of uncertainties

This paper continues the study (Yegorov, Dower, and Grüne et al.) and develops a curse-of-dimensionality-free numerical approach to feedback stabilization, whose theoretical foundation was built in Yegorov et al. and involved the characterization of control Lyapunov functions (CLFs) via exit-time optimal control. First, we describe an auxiliary linearization-based technique for the construction of

In this study, the control problem of trajectory tracking of mobile robots considering the difference between the center of mass and the geometric center is presented. In vehicles, sometimes the mass and geometric centers are not the same, which may be due to a load. In this case, the tracking error model is obtained for the first time. Then, this model is linearized around the reference trajectory

In this paper, we propose an event‐triggered decentralized optimal fault tolerant control (ETDOFTC) scheme based on adaptive dynamic programming for mismatched interconnected nonlinear systems with actuator failures. For fault‐free dynamic models, the decentralized control problem is addressed by developing a set of decentralized optimal control strategies for isolated subsystems with modified value

This article focus on the robust H∞ stability analysis and controller design for a class of uncertain and disturbed continuous‐time systems with input time‐varying delays characterized by stochastic Bernoulli distributions. First, robust H∞ stability conditions for linear continuous systems with interval input time‐varying delays is investigated. A delay‐distribution‐approach is considered to reduce

This work presents the results of experimental operation of a solar‐driven climate system using mixed‐integer nonlinear model predictive control (MPC). The system is installed in a university building and consists of two solar thermal collector fields, an adsorption cooling machine with different operation modes, a stratified hot water storage with multiple inlets and outlets as well as a cold water

This article is concerned with the optimal linear‐quadratic‐Gaussian control problem for discrete‐time linear systems corrupted by white and time‐correlated measurement noises. First, an optimal predictor for the system under consideration is proposed. Then, an optimal controller is designed, which minimizes an expected loss by a control strategy where the control is a function of measurement sequence

This paper is concerned with large‐angle attitude tracking control for quadrotors in the presence of time‐varying inertia and external disturbances using a switched linear parameter‐varying (LPV) system method. The attitude system of the quadrotor is divided into two parts, that is, the outer attitude‐angle loop and inner angular‐velocity loop. A feedback linearization controller is designed in the

In this article, we propose the issue of H∞ deconvolution filtering for two‐dimensional (2D) systems described by the Fornasini–Marchesini local state‐space model. The main challenge is the design of a deconvolution filter to rebuild the 2D signal so that the filter error system is asymptotically stable and preserves a guaranteed H∞ performance. To overcome this issue, we use some free matrix variables

This work studies the problem of constructing control Lyapunov functions (CLFs) and feedback stabilization strategies for deterministic nonlinear control systems described by ordinary differential equations. Many numerical methods for solving the Hamilton–Jacobi–Bellman partial differential equations specifying CLFs typically require dense state space discretizations and consequently suffer from the

In this article, the problems of robust reliable H∞ optimization control for discrete‐time nonlinear systems with or without time‐delay subject to faults are investigated. A static state feedback controller is explored for Takagi–Sugeno fuzzy systems against nonlinear dynamics, exogenous disturbances, and model uncertainties. In contrast to the design of conventional controllers, the proposed controller

In this paper, we investigate H∞ leader‐following consensus of multi‐agent systems with state multiplicative noise governed by stochastic differential equations and random time‐varying input delays which satisfy a certain probability. A new predictor‐based controller is designed based on the reduction approach to guarantee H∞ leader‐following consensus is achieved in mean square sense. By designing

In this note, we present some complementary results on the infinite horizon optimal control for linear time‐delay systems. We formally establish some properties of the matrices arising in the Bellman functional, and we prove that any admissible linear control law generates only a class of Bellman functional for addressed systems. Additionally, experimental results are presented, which illustrate a

This article studies a class of dynamic optimization of large‐population system in which a large number of negligible agents are coupled via state‐average in their cost functional and state dynamics. The most significant feature in our setup is the dynamics of individual agents are modeled by forward–backward stochastic differential equations. The associated mean‐field game, in its forward–backward

This paper proposes a new analytical tuning strategy for Model Predictive Control (MPC). In the proposed approach, MPC tuning problem is restated as a pole‐zero placement problem. New analytically tuning equations are given and a deep study on the places of poles and zeros of the closed‐loop system is performed. It is known that, appropriate zero placement can improve the robust stability of the closed‐loop

This article describes a control approach for large‐scale electricity networks, with the goal of efficiently coordinating distributed generators to balance unexpected load variations with respect to nominal forecasts. To mitigate the difficulties due to the size of the problem, the proposed methodology is divided in two steps. First, the network is partitioned into clusters, composed of several dispatchable

A mesh refinement method is described for solving optimal control problems using Legendre‐Gauss‐Radau collocation. The method detects discontinuities in the control solution by employing an edge detection scheme based on jump function approximations. When discontinuities are identified, the mesh is refined with a targeted h‐refinement approach whereby the discontinuity locations are bracketed with

Nonsmooth dynamics driven by stochastic disturbance arise in a wide variety of engineering problems. Impulsive interventions are often employed to control stochastic systems; however, the modeling and analysis subject to execution delay have been less explored. In addition, continuously receiving information of the dynamics is not always possible. In this article, with an application to an environmental

This article develops a general framework for preference heterogeneity. This framework includes a discount function, a nonstandard Hamilton–Jacobi–Bellman equation (HJB) and a behavioral equation. When controlling parameters, our discount function and its HJB can reduce to those in Marín‐Solano and Patxot (2012) and among many others. In various fields, our framework can find equilibrium path in the

We study existence and approximation of optimal controls for systems governed by McKean‐Vlasov stochastic differential equations. It is well known in simple examples that in the absence of convexity conditions, the strict control problem has no optimal solution. The compactification of the set of such strict admissible controls leads to measure valued controls called relaxed controls. The space of

The main goal of this article is to study a general augmented Lagrangian method for optimal control problems governed by mixed (quasi‐)equilibrium problems. We establish zero duality gap properties between a primal problem and its augmented Lagrangian dual problem. As a consequence, we give some existence results for optimal control problem governed by evolutionary quasi‐variational inequalities. An

This article is concerned with the guaranteed cost control problem for a class of fractional‐order (FO) uncertain delayed linear systems with norm‐bounded time‐varying parametric uncertainty. Based on whether the states are available or not, guaranteed‐cost state‐based feedback stabilization and guaranteed‐cost observer‐based feedback stabilization for such system are addressed, respectively. By employing

This article introduces a new class of basis functions, namely, the generalized Bernoulli polynomials (GBP). The GBP are adopted for solving nonlinear fractional optimal control problems (NFOCP) generated by nonlinear fractional dynamical systems (NFDS) and boundary conditions (BC). The corresponding operational matrices (OM) of fractional derivatives (FD) expand the solution of the problem in terms

A co‐infection model for oncogenic human papillomavirus (HPV) and tuberculosis (TB), with optimal control and cost‐effectiveness analysis is studied and analyzed to assess the impact of controls against incident infection and against infection with HPV by TB‐infected individuals as well as optimal TB treatment in reducing the burden of the co‐infection of the two diseases in a population. The co‐infection

Due to the increasing number of automated guided vehicles (AGVs) in the multi‐AGV system and the limitation of working environment, path conflicts often occur in the working process of AGVs, which affects the working efficiency of the multi‐AGV system. Thus, a optimization method by arranging the AGVs' traffic sequence is proposed in this paper. First, an AGV working map is reconstructed with graph

This paper is concerned with the optimal H2 filtering problem for continuous‐time systems with multiplicative noise and multiple sampled delay measurements. The reorganized observation technique is firstly applied for treating the sampled delay terms, and then an equivalent delay‐free sampled measurement is received. An optimal H2 filter is constructed by using a dynamic model with finite jumps, which

Many process control problems encapsulate multiple and often conflicting objective criteria spanning different levels of relative importance. In this paper, we consider a class of multi‐objective receding horizon optimal control problems and propose a novel multi‐objective model predictive control (MO‐MPC) scheme for nonlinear systems subject to constraints and several prioritized (economic) criteria

This paper revisits the problem of H∞ filter design for singular systems with interval time‐varying delays. Firstly, by state decomposition method (SDM), a novel Lyapunov–Krasovskii functional (LKF) including two augmented nonintegral terms is presented. Secondly, via the constructed LKF and the linear matrix inequality (LMI) technique, sufficient stability conditions with lower conservatism are achieved

This paper focuses on a new state‐feedback control synthesis for discrete‐time polytopic linear parameter‐varying (LPV) systems. The synthesis conditions have been derived using an approach less conservative than those currently found in the literature, which allows to deal with polytopic LPV systems subject to time‐varying parameters in all matrices of its state‐space representation. Based on parameter‐dependent

We construct an algorithm for solving a constrained optimal control problem for a first‐order evolutionary system governed by a positive self‐adjoint operator. The problem consists in identifying distributed control that minimizes a given cost functional, which comprises a cost of the control and a trajectory regulation term, while steering the final state close to a given target. The approach explores

In this work, we present a robust Model Predictive Control (MPC) strategy based on linear matrix inequalities (LMIs) for the intravenous administration of Propofol, a drug which is used for anesthesia during surgeries. The controller is designed for a population of patients and takes into account constraints on the amount of administered drug and on the drug concentration profile. A detailed compartmental

This article presents a method for designing stabilizing terminal‐costs for linear model predictive controllers whose stage‐costs are a mixture of weighted 1‐norms and ∞‐norms of the system states and inputs. This problem is abstracted by replacing the 1/∞‐norm stage‐costs with convex Minkowski functions. We show that a convex Minkowski terminal‐cost is a control Lyapunov function if and only if the

In this article, we study a kind of linear quadratic optimal control problem driven by forward–backward stochastic differential equations (FBSDEs in short) with deterministic coefficients. The cost functional is defined by the solution of FBSDEs. By means of the Girsanov transformation, the original issue is turned equivalently into the classical LQ problem. By functional analysis approach, some necessary

We present a new numerical indirect method to solve optimal control problems with degenerate equilibrium points. When the optimal control problem is autonomous, the corresponding canonical system becomes an autonomous system of ordinary differential equations. Combining the well‐known blow‐up technique of vector fields with the classic backward integration method, and focusing on a specific type of

In this article, we assume that the insurer can purchase per‐loss reinsurance and invest its surplus in a financial market consisting of a risk‐free asset and a risky asset. It is also assumed that the investment amount of the risky asset is capped at a fixed level and that short‐selling is prohibited. Our objective is to minimize the probability of absolute ruin, and the reinsurance premium is computed

This paper is concerned with a mixed optimal control problem driven by forward‐backward stochastic differential equation, where the term “mixed” means that there are two controllers, one is a deterministic controller and the other is a random controller. We derive a necessary condition and a sufficient condition for the mixed optimal control problem. A linear‐quadratic mixed optimal control problem

We investigate in this article Pontryagin's maximum principle for a class of control problems associated with a Cahn–Hilliard–Navier–Stokes model in a two dimensional bounded domain. The model consists of the Navier–Stokes equations for the velocity v, coupled with a Cahn–Hilliard model for the order (phase) parameter . We derive Pontryagin's maximum principle for the control problems assuming that

In this work, we investigate the quadratic bilinear optimal control. We first review the case of finite‐time interval, and then focus on the case of infinite‐time horizon. The main difficulty in solving a quadratic optimal control for bilinear systems is the non‐convexity of the cost function, which due to the fact that the dependence of the state with respect to the control is highly nonlinear. Then

Unfalsified adaptive control (UAC) is a class of switching control systems which deals with the control of uncertain systems. The UAC includes a bank of controllers, a supervisor, and a system in which the supervisor selects a stabilizing controller based on the system input and output data. Feasibility is the only assumption required in the UAC strategy, which guarantees that there is at least one

The integration of nonrenewable and renewable energy resources is growing rapidly due to energy demand and smart grid technologies. In power grids, the performance of synchronization is reduced by some issues such as frequency instability, voltage distortion, and voltage unbalance. This work presents the fast synchronization of the PV grid‐connected system utilized the hybrid optimized proportional

In this paper, the robust sampled‐data input mixed H2/H∞ performance control of uncertain T‐S fuzzy systems with time delay and aperiodic sampled‐data state feedback input is considered. Some delay‐dependent linear matrix inequality‐based criteria are proposed to guarantee the H2 performance by the design of robust H∞ control. The novel aperiodic sampled‐data parallel distributed compensator is developed

A modified pseudospectral (PS) method is presented based on direct Legendre interpolation for unconstrained optimal control problems (OCP). The conditions for the convergence of the proposed PS method are provided and it is proved that the method possesses the spectral accuracy for solutions in appropriate Sobolev spaces. Different from existing convergence results in the literature, in this new analysis

In this article, we are concerned with the ‐finite‐time stabilization (‐FTS) with optimal performance for the continuous‐time system. The definition of ‐FTS is first proposed. The main contribution is to give the equivalent conditions for the open‐loop solvability and sufficient conditions for the closed‐loop solvability of the ‐FTS problem with optimal performance for the finite‐time interval. Moreover

In this article, the robust fusion steady‐state filtering problem is investigated for a class of multisensor networked systems with mixed uncertainties. The uncertainties include state‐dependent and noise‐dependent multiplicative noises, missing measurements, packet dropouts, and uncertain noise variances, the phenomena of missing measurements and packet dropouts occur in a random way, and are described

This study investigates the use of trigonometric functions to resolve two major issues encountered when solving practical optimal control problems (OCPs) that are characterized by nonlinear controls. First, OCPs with constraints on nonlinear controls require the solution to a multipoint boundary value problem, which poses additional computational difficulties. Second, in certain unconstrained OCPs

This article is concerned with the event‐triggered nonfragile reliable control of nonlinear positive semi‐Markovian jump systems with randomly occurring faults. The randomly occurring actuator fault, describing the phenomenon of the actuator fault appearing in a random way, is assumed to obey a semi‐Markovian process different from the jump process of the systems. The nonlinear function is located

This article investigates the generalized Nash equilibrium (GNE) seeking for the game with equality constraints. Each player cannot directly access all the other player's actions and the gradients of all players' payoff functions are unknown. In these scenarios, an interesting question is under what distributed algorithm the GNE can be found. To address such games, we first design a two‐time‐scale

Hybrid systems have been attracting considerable attention in recent years because of their ability to model complex physical systems with both continuous and discrete dynamic behavior. When controlling such complex systems, a ubiquitous problem is the presence of large parametric uncertainties. Adaptive control has been used in recent years for hybrid systems to cope with parametric uncertainties

In this paper, guaranteed cost control for a class of switched linear systems subject to time delays is investigated, where a nonweighted quadratic performance index is considered. In particular, a novel quasi‐time‐dependent Lyapunov‐Krasovskii function based on a time‐varying positive definite matrix is proposed that is decreasing during the switching intervals and at the switching instants. By exploiting

In this article, an algorithm is presented for solving the optimal control problem for the general form of a hybrid switching system. The cost function comprises terminal, running and switching costs. The controlled system is an autonomous hybrid switching system with jumps either at some switching times or some time varying switching manifolds. The proposed algorithm is an extension of the first‐order

A new type of fast distributed Kalman consensus filtering algorithm based on local information feedback is presented to tackle filtering problems in wireless sensor networks. First, this fast filtering issues are transformed into a stochastic stability problem of the dynamic estimation errors, which can be solved by Lyapunov's second method and matrix theory. Then, two sufficient conditions about the

In this work, a minimum variance estimator is designed for a networked system with inherent network imperfections in both sensor to estimator (S‐E) and controller to actuator (C‐A) channels simultaneously. The channels are affected by packet delays, dropouts, and uncertain observations. These effects are modeled using five Bernoulli distributed random variables. Correlation of noise at neighboring

This article is concerned with the tracking of nonequilibrium motions with model predictive control (MPC). It proposes to parametrize input and state trajectories of a dynamic system with basis functions to alleviate the computational burden in MPC. As a result of the parametrization, an optimization problem with fewer variables is obtained, and the memory requirements for storing the reference trajectories