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

In this paper, the nonlinear robust reference tracking problem is considered and an Improved Two‐Loop Nonlinear Model Predictive Control (ITL‐NMPC) design is proposed for a pre‐controlled system with bounded uncertainties subject to input and state constraints. In the industry, this scheme leads the lower design cost and fewer implementation risks since (i) it allows the existing controller to remain

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

In this article, we address the task of setting up an optimal production plan taking into account an uncertain demand. The energy system is represented by a system of hyperbolic partial differential equations and the uncertain demand stream is captured by an Ornstein‐Uhlenbeck process. We determine the optimal inflow depending on the producer's risk preferences. The resulting output is intended to

Beltratti et al proposed an environmental sustainability problem and stressed the importance of two related control problems, namely, the discounted utilitarian problem and the long‐run utility problem. From the analysis of the latter, they obtained the definition of the Green Golden Rule (GGR). We discuss the optimal steady‐state solutions of the first problem and provide new results, completing the

In this article, searching the general Nash equilibrium in the noncooperation game is discussed under the general constraints of containing bounded constraint, coupled equality constraint, and private inequality constraint. Meanwhile, the continuous‐time event‐triggered distributed subgradient projective algorithm (C‐ETDSP algorithm), to greatly cut down the number of communication flows, is designed

This article presents novel schemes using which a robustly stable and feasible optimal controller can be obtained for uncertain vibrational systems. Furthermore, the aforementioned objectives are satisfied solely employing a rigid approximation of continuum mechanics systems. Simultaneously, significant reductions in control complexity and computation burden are attained. On this basis, a new model

Design of feedback control by an optimal control approach relies on the solutions of the Hamilton‐Jacobi‐Bellman (HJB) equation, while this equation rarely admits analytical solutions for arbitrary choices of the performance measure. An inverse optimal feedback design approach is proposed here in which analytical solutions are explored for the HJB equation that optimize some meaningful, but not necessarily

This article deals with the problems of stability and stabilization for a class of discrete‐time switched systems with time‐varying delay under arbitrary switching signal. First, sufficient conditions guaranteeing the asymptotic stability of the unforced system are developed, by using the switched Lyapunov‐Krasovskii functional method. Then, based on the obtained results, a state feedback controller

The aim of this article is to investigate an efficient computational method for solving distributed‐order fractional optimal control problems. In the proposed method, a new Riemann‐Liouville fractional integral operator for the Bernstein wavelet is given. This approach is based on a combination of the Bernstein wavelets basis, fractional integral operator, Gauss‐Legendre numerical integration, and

A method is developed to numerically solve chance constrained optimal control problems. The chance constraints are reformulated as nonlinear constraints that retain the probability properties of the original constraint. The reformulation transforms the chance constrained optimal control problem into a deterministic optimal control problem that can be solved numerically. The new method developed in

In this article, we study a type of fully coupled mean‐field forward‐backward stochastic differential equations with jumps under the monotonicity condition, including the existence and the uniqueness of the solution of our equations as well as the continuity property of the solutions with respect to the parameters. Then we establish the stochastic maximum principle for the corresponding optimal control

This article investigates the optimal output feedback control problem for discrete‐time Markov jump linear system (MJLS) with input delay and packet losses in finite horizon. There are three main contributions. First, we assume that the state variable and the jump variable are available to the controller, and then we propose a new version of stochastic maximum principle. Based on the new proposed tool

In this article, a suboptimal nonlinear discrete control sequence for nonlinear discrete affine control systems is proposed. Using the dynamic programming approach in discrete time domain, the suboptimal control sequence is obtained in every step considering a quadratic performance index of finite horizon. The proposed control strategy is applied to improve the dynamic and energetic performances of

Minimum time solar sailing trajectories are introduced using a combination of indirect and direct optimal control techniques. Here, large‐scale, multiphase optimal control problems are solved using a pseudospectral collocation technique applied to an orbital debris mitigation concept. These solutions are obtained for realistic sail dimensions, producing multirevolution, Earth‐centered trajectories

This article presents an efficient numerical method for solving fractional optimal control problems (FOCPs) by utilizing the Hermite scaling function operational matrix of fractional‐order integration. The proposed technique is applied to transform the state and control variables into nonlinear programming (NLP) parameters at collocation points. The NLP solver is then used to solve FOCP. Furthermore

This article is concerned with the stochastic recursive optimal control problem with mixed delay. The connection between Pontryagin's maximum principle and Bellman's dynamic programming principle is discussed. Without containing any derivatives of the value function, relations among the adjoint processes and the value function are investigated by employing the notions of super‐ and sub‐jets introduced

This article presents an alternating direction method of multipliers (ADMM) algorithm for solving large‐scale model predictive control (MPC) problems that are invariant under the symmetric‐group. Symmetry was used to find transformations of the inputs, states, and constraints of the MPC problem that decompose the dynamics and cost. We prove an important property of the symmetric decomposition for the

Parametric uncertainties and the problems associated with the design of robust state feedback control tends to be a major concern for achieving stable operation of nonlinear systems. To overcome these drawbacks, this article provides a perspective on a randomized algorithm based probabilistic control for nonlinear systems. The control approach aims at development of randomized algorithms for control

This article investigates the optimal control problem of nonzero sum game mean‐field delayed Markov regime‐switching forward‐backward stochastic system with Lévy processes associated with Teugels martingales over the infinite time horizon. Based on the transversality conditions, assumption of convex control domain, infinite‐horizon version of stochastic maximum principle (Nash equilibrium), and necessary

In this article, considering one type of fuzzy discrete‐time networked control systems (NCSs) under stochastic communication protocol (SCP), a fuzzy‐based nonfragile H∞ filter is developed to detect the subsistent fault signal. The Takagi‐Sugeno (T‐S) mathematical model is employed to approximate the nonlinearities in the concerned fuzzy NCSs. The SCP is adopted to decide which sensor gets the access

This study, under zero initial condition, aims to characterize the reachable set bound for a class of neutral Markovian jump systems (NMJSs) with interval time‐varying delays and bounded disturbances. To begin with, the time‐delays are considered to be mode‐dependent while delay mode and system mode are different. By utilizing free‐weighting matrix method and reciprocally convex combination technique

A derivative‐free estimator was introduced to alleviate the drawbacks of the conventional Kalman filter when performing nonlinear analyses under different circumstances. In this work, the scaled Unscented Kalman Filter, Divided Difference Kalman filter, and Cubature Kalman filter (CKF) were selected to investigate the effectiveness of these filters in predicting the states of a complex semi‐batch reaction

This paper researches the static output‐feedback stabilization of single‐input single‐output (SISO) positive coupled differential‐difference equations (CDDEs) with unbounded time‐varying delays. First, a necessary and sufficient condition is provided for the positivity and asymptotical stability of CDDEs with unbounded time‐varying delays. For this type of system, based on the constructed estimates

This work presents a multivariable predictive controller applied on a redundant robotic manipulator with three degrees of freedom. The article focuses on the design of a discrete model‐based predictive controller (DMPC) using the Laguerre function as a control effort weighting method to enhance the solution of Hildreth's quadratic programming and to minimize the trade‐off problem in constrained case

This article addresses the problem of distributed controller design for linear discrete‐time systems. The problem is posed using the classical framework of state feedback gain optimization over an infinite‐horizon quadratic cost, with an additional sparsity constraint on the gain matrix to model the distributed nature of the controller. An equivalent formulation is derived that consists in the optimization

This article presents an optimal control strategy (OCS) for semiactive vehicle suspensions with road profile sensors. The suspension is modeled as a quarter‐car model with a magnetorheological (MR) damper. The OCS main objective is to minimize the fourth‐power acceleration of the sprung mass. In addition, three pointwise constraints of the model are taken into account when the optimal control problem

In this paper, we study fractional‐order optimal control problems (FOCPs) involving the Atangana‐Baleanu fractional derivative. A computational method based on B‐spline polynomials and their operational matrix of Atangana‐Baleanu fractional integration is proposed for the numerical solution of this class of problems. With this numerical technique, the FOCPs are reduced to a system of equations which

In this present contribution, an attempt has been taken to design and analyze the performance of elephant herding optimization (EHO) based controller for load frequency control (LFC) applications of interconnected power system. The studied system is a two‐area nonreheat thermal interconnected system which is widely used in literature. A proportional‐integral‐differential controller is utilized for

This research provides a new framework based on a hybrid of block‐pulse functions and Legendre polynomials for the numerical examination of a special class of scalar nonlinear fractional optimal control problems involving delay. The concepts of the fractional derivative and the fractional integral are employed in the Caputo sense and the Riemann‐Liouville sense, respectively. In accordance with the

The main purpose is the study of optimal control problem in a domain with rough boundary for the mixed Dirichlet‐Neumann boundary value problem for the strongly nonlinear elliptic equation with exponential nonlinearity. A density of surface traction u acting on a part of rough boundary is taken as a control. The optimal control problem is to minimize the discrepancy between a given distribution and

Time‐space network (TSN) models have been widely used for collision‐free path planning of automated guided vehicles. However, existing TSN models are planned globally. The global method suffers from computational complexity and uncertainties cannot be dealt with in the dynamic environment. To address these limitations, this article proposes a new methodology to decompose the global planning problem

In this article, we study the open‐loop and closed‐loop solvability for indefinite mean‐field stochastic linear quadratic (MF‐SLQ) optimal control problem and its application in finance, where the controlled stochastic system is driven by a Brownian motion and a Poisson random martingale measure and also disturbed by some stochastic processes. The intrinsic property of stochastic systems results in

A new mathematical model of tuberculosis (TB) featuring exogenous re‐infection and incomplete treatment is presented and analyzed. The model divides total population into susceptible, latently infected, actively infected (uninformed and enlightened), and treatment classes. The model with or without incomplete treatment exhibits backward bifurcation phenomenon, which is caused by the presence of exogenous

This article is concerned with the design and performance optimization of feedback controllers for state‐based switching bilinear systems (SBLSs), where subsystems take the form of bilinear systems in different state space polyhedra. First, by further dividing the subregions into smaller regions and designing region‐dependent feedback controllers in the resulting regions, the SBLSs can be transformed

Model predictive control (MPC) for linear dynamical systems requires solving an optimal control structured quadratic program (QP) at each sampling instant. This article proposes a primal active‐set strategy, called PRESAS, for the efficient solution of such block‐sparse QPs, based on a preconditioned iterative solver to compute the search direction in each iteration. Rank‐one factorization updates

Up to now, several numerical methods have been presented to solve finite horizon fractional optimal control problems by researchers, while solving fractional optimal control problems on infinite domain is a challenging work. Hence, in this article, a numerical method is proposed to solve fractional infinite horizon optimal control problems. At the first stage, a domain transformation technique is used

A batch to batch optimal control strategy based on multiinput multioutput adaptive hinging hyperplanes (MIMO AHH) prediction and Kalman filter correction is proposed for the products quality control of the batch process. The model of AHH is one kind of piecewise linear models and is extended to the MIMO case in this article. The MIMO AHH is then used to develop the predictive model of the batch process

For partially interdependent networks composed of two subnetworks, the finite‐time optimal pinning control problem is investigated. Among them, only a part of the nodes between the two subnetworks are interdependent on each other. In the network, the coupling relationship between any two nodes of the network is a continuous nonlinear function. Based on the pinning control, the optimal control theory

In this article, we study second‐order necessary optimality conditions for a discrete optimal control problem with a nonconvex cost function, nonlinear state equations and mixed constraints. In order to achieve these conditions, we first establish an abstract result on the second‐order necessary optimality conditions for a mathematical programming problem and then we derive the second‐order necessary

This article addresses a robust control problem of time‐varying stochastic systems with time‐delays. Through Linear Parameter Varying (LPV) modeling approach, the time‐varying parameters can be described via the convex combination. Therefore, the LPV stochastic system is interpreted by a weighting function and multiplicative noised linear systems. Furthermore, stabilization problem for the systems

When the observation equation of system has not been verified or corrected under certain environmental conditions, applying it will yield to unknown system error and filtering error. The unknown system error can be effectively eliminated by introducing the incremental equation. In this article, the local Kalman estimator for the incremental system with correlated noises is first presented. It solves

This work is concerned with the H∞ state‐feedback control for the discrete‐time Markovian jump systems with incomplete knowledge of transition probabilities. A less conservative criterion is proposed via linear matrix inequalities (LMIs) such that the considered systems are stochastically stable and have a prescribed H∞ disturbance attention level. Furthermore, based on the obtained results, a state‐feedback

To promote artificial rain in India and other such developing countries, in this article, we have proposed and analyzed a nonlinear mathematical model for cloud seeding by considering that aerosols are introduced proportional to the density of water vapors present in the atmosphere. The model is analyzed using Lyapunov's stability theory of differential equations. To reduce the cost of cloud seeding

In this paper, the problem of social distancing in the spread of infectious diseases in the human network is extended by optimal control and differential game approaches. Hear, SEAIR model on simulation network is used. Total costs for both approaches are formulated as objective functions. SEAIR dynamics for group k that contacts with k individuals including susceptible, exposed, asymptomatically infected

This article is devoted to the study of a controlled population of cells. The modeling of the problem leads to a mathematical formulation of stability and reachability properties of some controlled systems under uncertainties. We use the Hamilton‐Jacobi approach to address these problems and to design a numerical method that we analyze on several numerical simulations.

In this paper, we introduce a necessary and sufficient condition of optimality for a new class of multidimensional optimal control problems governed by path‐independent curvilinear integral functionals and mixed constraints involving first‐order partial differential equations (PDEs) of m‐flow type. Furthermore, as a consequence, we establish the equivalence between the class of (strongly) b‐invex functionals