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

Here, we propose a novel nonfragile predictive control method for an omnidirectional rehabilitative training walker. The aim of the study was to design a tracking controller that includes simultaneous constraints on the tracking errors in the position and velocity in order to guarantee safe system states for the omnidirectional walker. The nonfragile controller uses incremental control to solve the

In this article, we study the robust solution set of a multitime first‐order PDE constrained control optimization problem with data uncertainty (MCOPU) and an unconstrained multitime control optimization problem (MCOPU)ρ . We establish the equivalence between a robust optimal solution of (MCOPU) and a robust minimizer of (MCOPU)ρ under the appropriate assumptions. Furthermore, we define the uncertain

The micro machine tool that can produce nanostructures by force modulation approach plays a significant role in nanotechnology. In this paper, to guarantee fast and high‐precision cutting subject to external disturbances and input saturation, a robust model predictive control (MPC) using a tube‐based method is exploited to develop a controller for the machining system consisting of a piezoelectric

In this work, the problem of regulating blood glucose (glycemia) in type I diabetic patients is studied by means of an impulsive zone model predictive control (iZMPC), which bases its predictions on a novel long‐term glucose‐insulin model. Taking advantage of the impulsive version of the model—which features real‐life properties of diabetes patients that some other popular models do not—the given control

In this article, the H ∞ tracking control problem is first considered for two‐dimensional fuzzy networked control systems. The system is described by fuzzy blending of the so‐called second Fornasini‐Marchesini local linear state‐space model. Based on the fuzzy model, an observer‐based state feedback controller is employed to guarantee the H ∞ tracking performance. The separation property is established

In this article, a starting control problem with two intermediate moments of observation in the mixed linear problem for the second‐order hyperbolic equation with quadratic functional is studied. The necessary and sufficient optimality conditions are obtained in the form of variational inequality.

In this article, a novel intermittent projected subgradient algorithm is presented to solve the randomized optimal consensus problem for heterogeneous multiagent systems with time‐varying communication topologies. The multiagent systems achieve the consensus meanwhile minimizing the global objective function via the proposed algorithm, where f i (x ) is the convex objective function of agent i itself

By going to millimeter wave (mmWave) we can use large scale MIMO due to short mmWave wavelength to overcome path loss by using beamforming to focus power of signal to the receiver. System structure of mmWave band is different with conventional MIMO because of large scale MIMO which is leading to use many RF‐chains. For this reason Hybrid structure have been proposed for large Scale MIMO. By going to

This article addresses the adaptive fuzzy finite‐time control problem for a class of switched nonlinear systems whose powers are positive odd rational numbers and vary with the switching signal. The fuzzy logic systems (FLSs) are used to approximate the unknown nonlinearities of the controlled systems, and then by combining backstepping control algorithm with adding a power integrator technique, an

This article investigates the distributed adaptive consensus tracking control problem for a class of high‐order nonlinear multiagent systems with unmodeled system dynamics, uncertain external disturbances, and event‐triggered communication. Under an undirected graph condition, a robust distributed adaptive consensus control scheme is proposed. To deal with the lumped system uncertainties involved in

This article proposes a Fuzzy Second Order Integral Terminal Sliding Mode (FSOITSM) control approach for DFIG‐based wind turbines subject to grid faults and parameter variations. Since traditional terminal sliding mode control (SMC) suffers from singularity, a novel integral terminal sliding manifold is proposed to eliminate chattering and improve the wind turbine's performance in the presence of faults

This article bestows the linear quadratic Gaussian (LQG)/Loop Transfer Recovery (LTR) optimal controller design for a perturbed linear system having insufficient information about systems states through a multiobjective optimization approach. A Kalman filter observer is required to estimate the unknown states at the output from the noisy data. However, the main downside of the LQG controller's is that

The present article is a study of an optimal control problem having a non‐differentiable, but Lipschitz, cost function. It is inspired by the minimisation of the energy consumption of a car‐like vehicle or robot along a road which profile is known. This problem is stated by means of a simple model of the longitudinal dynamics and a running cost that comprises both an absolute value function and a function

This article explores the impact of regular perturbations (ie, small terms) in input constrained optimal control problems for nonlinear systems. In detail, it is shown that perturbation terms of magnitude ε appearing in the dynamics or the cost function lead to a variation of magnitude Kε 2 in the optimal cost. The scale factor K can be estimated from the nominal (ε =0) solution and the analytic expressions

We study the optimal control of district heating networks using a reduced order model based on a system theoretic description close to the underlying Euler equations. In the presented scenarios, the central task is to limit the maximal feed‐in power occurring as a product of control and state variables. The underlying dynamics of heating networks acting as optimization constraints pose the central

A recent river environmental restoration problem is approached from a standpoint of stochastic control of hybrid regime‐switching diffusion processes with discrete and costly observations. This setting harmonizes with real problems because continuously obtaining environmental and ecological information is difficult, and is often costly. The main problem is to decide when and how much of the sediment

Earth pressure balance (EPB) shield tunneling machine has been widely used in underground construction. To avoid the catastrophic accidents caused by earth pressure imbalance, the earth pressure on excavation face must be controlled balance to that in chamber. To solve this problem better, a multi‐variable data‐driven optimal control method for shield machine based on dual‐heuristic programming (DHP)

We derive space‐time a posteriori error estimates of finite element method for linear parabolic optimal control problems in a bounded convex polygonal domain. To discretize the control problem, we use piecewise linear and continuous finite elements for the approximations of the state and costate variables, whereas piecewise constant functions are employed for the control variable. The temporal discretization

This paper presents a mixed‐integer model predictive controller for walking. In the proposed scheme, mixed‐integer quadratic programs (MIQP) are solved online to simultaneously decide center of mass jerks, footsteps positions, durations, and rotations while respecting actuation, geometry, and contact constraints. Most walking controllers require preplanned footstep rotations to avoid dealing with the

In this article, we consider the optimal topology design and distributed formation control problem of multiagent systems (MAS) with complex‐weighted directed topology. First, a framework is proposed to associate optimal topology of MAS to a constrained optimization problem with a complex Laplacian matrix, which is independent of the agent dynamics. The main contribution of the proposed approach compared

In the article, we derive an existence theorem for a Bolza problem described by a nonlinear integro‐differential system of Volterra type. We use an approach based on the lower closure theorem for orientor fields due to Cesari and measurable selection theorem of Fillipov type due to Rockafellar. Paper is a continuation of [D. Idczak, S. Walczak, Necessary optimality conditions for an integro‐differential

This study discusses an efficient method of the Hopf bifurcation control for nonlinear aeroelastic system. The nonlinear aeroelastic system whose linear part has multiple non‐semi‐simple eigenvalues at critical point gives rise to Hopf bifurcations. The method of the multiple scales and the well‐known linear quadratic regulator method are used to deal with the optimal control of the nonlinear system

In this article, we study the control of a Chikungunya epidemic model solving several optimal control problems. We implement three strategies to control the spread of the Chikungunya virus in the human and vector population. The first control strategy is an educational campaign promoting the use bednets, avoiding water stagnation, wearing long sleeved shirts, among others. The second is treatment of

This article studies reachable set estimation for parameter uncertain systems with time delay. A new reachable set estimation method is proposed for nonlinear discrete‐time systems with parameter uncertainty and unknown but bounded disturbance. By analyzing Lyapunov‐Krasovskii functional, reachable set estimation is formulated to an optimization problem in terms of linear matrix inequalities. The proposed

In this work, we derive an a priori error estimate of order for the finite element approximation of a sparse optimal control problem governed by an elliptic equation, which is controlled in a finite dimensional space. Furthermore, box‐constrains on the control are considered and finitely many pointwise state‐constrains are imposed on specific points in the domain. With this choice for the control space

This paper addresses a pole‐assignment control problem for discrete‐time linear parameter varying (LPV) systems. Based on LPV modeling approach, time‐varying systems can be mathematically described via combining several linear systems and a specific weighting function. For the LPV systems, gain‐scheduled (GS) control scheme is applied to deal with stabilization problem subject to pole‐assignment constraint

Electric Vehicles (EVs) are gradually replacing conventional vehicles as they are environmentally friendly and cause less pollution problems. Unregulated charging has severe impacts on the distribution grid and may incur EV owners higher charging costs. Therefore, controlled charging infrastructures to supply the charging needs of large numbers of EVs are of vital importance. In this article, an optimal

This paper aims to address the tracking control problem for the multi‐joint manipulator on a space robot subject to model uncertainties and external disturbances. A Gauss‐Newton interactive optimization algorithm is used to obtain the desired joint angle for each joint. In order to formulate the optimization problem, the Denaait‐Hartenberg (D‐H) method is employed to describe the model of the multi‐joint

This article proposes a new numerical approach for solving fractional optimal control problems including state and control inequality constraints using new biorthogonal multiwavelets. The properties of biorthogonal multiwavelets are first given. The Riemann‐Liouville fractional integral operator for biorthogonal multiwavelets is utilized to reduce the solution of optimal control problems to a nonlinear

This article deals with an optimal control problem governed by a system that models the dynamics of predator‐prey interactions. We study the minimization of the infective prey density. Furthermore, our purpose is here to establish the existence of weak solutions and derive some optimality conditions. Finally, the impact of the control terms are studied to get an insight of the predator‐prey model adopting

In this article, we discuss an infinite horizon optimal control of the stochastic system with partial information, where the state is governed by a mean‐field stochastic differential delay equation driven by Teugels martingales associated with Lévy processes and an independent Brownian motion. First, we show the existence and uniqueness theorem for an infinite horizon mean‐field anticipated backward

Dealing with the interpatient and the intrapatient variability in type 1 diabetes mellitus (T1DM) patient are the prominent control challenges in the development of the artificial pancreas system (APS). An APS consider a nonlinear patient model that has many state variables, but the reality is that out of the many states only glucose concentration is measurable till date without any complication and

This article considers robust fusion algorithms for linear system with multichannel stochastic multiplicative disturbance by using projection theorem and projection formula. Based on the centralized and distributed (feedback and no feedback) fusion strategies, we present optimal filtering fusion algorithms, optimal fixed‐interval smoothing fusion algorithms, and fixed‐interval deconvolution fusion

We introduce a mathematical model for the composting process in biocells. The model includes several phenomena, like the aerobic biodegradation of the soluble substrate by means of a bacterial population, the hydrolysis of insoluble substrate, and the biomass decay. We investigate the best strategies to reduce substrate components in minimal time by controlling the effects of cell oxygen concentration

This paper presents the use of passive dynamics to generate the sagittal plane references for a biped walker. In order to achieve an adjustable gait width, a neural network reference generator, trained with passive walking data on different slopes, was applied. The control algorithm was implemented with an Nonlinear Model Predictive Control (NMPC) strategy, in order to perform multiple‐input multiple‐output

In this article, a novel neural network (NN) optimal control approach using adaptive critic designs is developed for nonlinear discrete‐time (DT) systems with time delays. First, to eliminate the delay term of control input, a time‐delay matrix function is developed by designing a M network. Furthermore, the cost function is approximated by the critic NN, and the control signal can be obtained directly

This paper studies the optimal reinsurance‐investment problems for an insurance company where the claim process follows a Brownian motion with drift. It turns out that there is a region where the probability of drawdown, namely, the probability that the value of the insurer's surplus process reaches some fixed fractional value of its maximum value to date is positive. Then in the complementary region

This paper is concerned with the stochastic near‐optimal control problem for a regime‐switching diffusion model, where the control domains are convex. The controlled system is described by the Itô‐type stochastic differential equation (SDE) with a continuous‐time Markov chain, which possesses a finite state structure. Some new estimates for state and adjoint processes are obtained in the presence of

In this article, we propose a higher order neural network, namely the functional link neural network (FLNN), for the model of linear and nonlinear delay fractional optimal control problems (DFOCPs) with mixed control‐state constraints. We consider DFOCPs using a new fractional derivative with nonlocal and nonsingular kernel that was recently proposed by Atangana and Baleanu. The derivative possesses

We propose a framework tailored to robust optimal control (OC) problems subject to parametric model uncertainty of system dynamics. First, we identify a generic class of robust objective kernels that are based on the class of deterministic quadratic objectives. It is demonstrated how such kernels can be expressed as a function of the stochastic moments of the state and how the objective terms relate

This paper introduces a new methodology for the design of fixed‐order multi‐objective output feedback controllers. The problem comprises a set of linear matrix inequalities and an additional rank constraint. The primary idea is to classify convex subsets of the set of rank constrained matrices in such formulations, based on which two noniterative and relatively fast methods are developed. The proposed

In the fast developing electric power system network, ancillary services like automatic generation control (AGC) plays a vital and significant role to ensure good quality of power supply in the system. To distribute good quality of power, a hybrid AGC system along with an efficient and intelligent controller is compelled. So, in this article, a cascaded proportional‐integral (PI)‐proportional‐derivative

This article focuses on the problem of linear quadratic Gaussian (LQG) control for discrete time‐varying system with input delay and state/control‐dependent noises. When the state variables can be exactly observed, first, we obtain the maximum principle by applying the method of variation. Second, a nonhomogeneous relationship between the state and the costate is developed in virtue of the obtained

The second part of our study is devoted to an analysis of the exactness of penalty functions for optimal control problems with terminal and pointwise state constraints. We demonstrate that with the use of the exact penalty function method one can reduce fixed‐endpoint problems for linear time‐varying systems and linear evolution equations with convex constraints on the control inputs to completely

This note is concerned with the problem of stabilizing a class of linear continuous‐time systems with completely unknown system dynamics subject to input energy constraint. To deal with this problem, a model‐based low gain feedback law is designed firstly by establishing a special algebraic Riccati equation. Such a low gain feedback law can semiglobally stabilize the linear systems subject to input

In this article, a real‐time nonlinear model predictive idle speed controller based on multiparametric programming is designed for an SI engine. Idle speed is a crucial recurring condition in urban vehicles demanding proper control to avoid stall. As will be seen, the nonlinear model predictive control (NMPC) system designed, besides complying with the predefined constraints, demonstrates a far better

This article discusses the design of a hybrid fuzzy variable structure control algorithm combined with genetic algorithm (GA) optimization technique to improve the adaptive proportional‐integral‐derivative (PID) continuous second‐order sliding mode control approach (APID2SMC), recently published in our previous article in the literature. In this article, first, as an improved extension to APID2SMC

With the advent of intelligent transport, quadrotors are becoming an attractive solution while lifting or dropping of payloads during emergency evacuations, construction works, etc. During such operations, dynamic variations in (possibly unknown) payload cause considerable changes in the system dynamics. However, a systematic control solution to tackle such interchanging dynamical behavior is still

This paper extends a control system framework for the maintenance planning investment decision for building energy retrofitting. The interacting energy and reliability effects that are ignored by previous models are incorporated in the current study. A set of energy efficiency and population decay models with interacting parameters and decision variables are established, and a state‐space model with

This study proposes an effective adaptive dynamic surface control (DSC) method based on the radial basis function neural networks and the auxiliary system for hypersonic flight vehicle (HFV) systems in the presence of system uncertainties, external disturbances, and state variable and control input constraints. Firstly, to enhance the robustness of the system, the neural network is combined with the

Motivated by new aerospace applications, the condition of minimum‐energy achieving high accuracy of both terminal orbital injection and attitude angle is required for better navigation and observation. The stability of guidance command also needs to be improved considering the control system. In this article, an optimal guidance algorithm with an advanced numerical method of spacecrafts is proposed

This article investigates the robust estimation and observer‐based finite time sliding mode control problems for a class of switched systems with time‐delays and uncertainties. For the studied system model, a common sliding surface related to the estimated states is initially constructed. Then, a suitable sliding mode control law is designed to ensure the accessibility of sliding surface. By selecting

In this article, a model‐free off‐policy reinforcement learning algorithm is applied to address the optimal tracking problem based on multiplayer non‐zero‐sum games for discrete‐time linear systems. In contrast to the traditional method and the policy iteration method for solving the optimal tracking problems, the proposed algorithm operates with the system data rather than the knowledge of the system