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. The problem of analytical synthesis of the control acceleration for an unmanned aerial vehicle (UAV) during its flight along a complex trajectory, consisting of sequentially located horizontal flight sections, located at different heights relative to the earth's surface has been solved in the paper. The problem has been solved as an analytical definition of the optimal control of a linear non-stationary system for a specified minimized quality functional. The mathematical model of the system is presented in the form of differential equations of UAV motion in the vertical plane of a fixed coordinate system related to the earth's surface. A feature of the proposed methodology for solving the problem is the substantiation of the original form of the minimized functional and parameters included in the law of variation of the control acceleration obtained by known methods. As the components of the quality functional, the values of coordinates and velocity of the UAV are considered and they are specified at the corresponding points in space through which the UAV path must pass, in order to obtain the optimal curvature of the trajectory. The derived mathematical dependences make it possible to implement them on board of an aircraft and, ultimately, solve the problem of ensuring the minimum energy consumption when controlling an object (UAV). Computer simulation of the analytically obtained results in the form of the UAV flight trajectory and the processes of changing its acceleration and speed have shown the efficiency of the proposed technique and the prospects of its use at the initial stage of the synthesis of the UAV control system.

The synthesis of a control law for tracking a target informative path as a new approach to solving the problem of planning a flight experiment for identifying the aerodynamic characteristics of automatically controlled aircraft is proposed. The mathematical statement and the method for solving the synthesis problem are obtained. In the numerical experiment, it is shown that the identification accuracy on the synthesized control can be significantly improved compared to the identification accuracy on the optimal program test signal. [ABSTRACT FROM AUTHOR]

This research work presents an optimal energy management for a hybrid water pumping system driven by a photovoltaic generator (PVG) and a wind turbine. These two renewable energies are used as power generation sources, whereas a battery is added as an energy‐storing system, for the purpose of controlling the power flow and providing a constant load supply. The proposed management system, serve to guarantee the pumping system autonomy in a rural region where's no access to the electrical network. As a result, a maximum power point tracking (MPPT) controller is created based on the fuzzy Takagi–Sugeno (TS) model, ensuring maximum power transfer to the moto‐pump in spite of wind speed and insolation changes. The synthesis of MPPT control law involves TS fuzzy reference models which generate the desired trajectories to track. A supervisor has been developed for energy management and its major purpose is to effectively use the battery to satisfy the power load requirements, and that is by maintaining the state of charge (SOC) to extend the battery's life. Finally, simulation results have been done based on Matlab/Simulink with the aim of validating the efficiency of the proposed energy management supervisor. [ABSTRACT FROM AUTHOR]

This article presents the results of a numerical experiment and an analysis of temperature fields (coolers for gas) using cooling elements in the case study gas pipeline. An analysis of the temperature fields demonstrated several principles for the formation of a temperature field, which indicates the need to maintain a relative temperature for gas pumping. The essence of the experiment was to install an unlimited number of cooling elements on the gas pipeline. The purpose of this study was to determine at what distance it is possible to install cooling elements for the optimal gas pumping regime, regarding the synthesis of the control law and the determination of the optimal location and assessment of control error depending on the location of the cooling elements. The developed technique allows for the evaluation of the developed control system's regulation error. [ABSTRACT FROM AUTHOR]

A variant of the synthesis method for controlling a linear MIMO system by an output vector is developed that provides the given spectrum of a multidimensional dynamic system in the state space. It is based on the principle of duality of the task of controlling a MIMO system by a state vector and the task of constructing a state observer. The algorithm, without any changes, is applicable for both continuous and discrete cases of describing the mathematical model of the MIMO system, has no restrictions on specifying the spectrum's elements of the closed MIMO system, and allows us to obtain synthesis problems in analytical form and to parameterize the set of equivalent control laws with feedback. An example of an analytical synthesis of the control law of a hypothetical aircraft is given. [ABSTRACT FROM AUTHOR]

The spread of an infectious disease in a population is a random process when considering a small group of individuals. However, to a great group of individuals, the use of deterministic behavior is better. Based on these facts, in the literature, there were proposed stochastic and deterministic epidemic models. This work proposes a mixed compartmental epidemic model that allows stratifying the population into groups, considers demographic and environmental variability, presents an approximation to stochastic effects, and contemplates the network effects. The proposed model has a compact form to assist in the synthesis of the control law and parameters estimation strategies. Its objective is to overcome the difficulties encountered when used purely deterministic or purely stochastic models. In the end, to detail and verify the functioning of the proposed model, we present a set of flowcharts and simulations. [ABSTRACT FROM AUTHOR]

The solution of the problem of determining the trajectory control of the observation process of a mobile digital direction finder in the topology of a road network is considered when evaluating the spatial configuration of the system of discrete sources of radio emission. A quality criterion is proposed that allows using the principles of discrete dynamic programming in the synthesis of the control law. Its relationship with quality criteria based on the correlation matrices of estimation errors is determined. An example is given. [ABSTRACT FROM AUTHOR]

Introduction. This study presents a robust control method for the path following problem of the PUMA560 robot. The technique is based on the Adaptive Fuzzy Type-2 Fast Terminal Sliding Mode Control (AFT2FTSMC) algorithm and is designed to handle actuator faults, uncertainties (such as payload change), and external disturbances. The aim of this study is to utilize the Fast Terminal Sliding Mode Control (FTSMC) approach in order to ensure effective compensation for faults and uncertainties, minimize tracking error, reduce the occurrence of chattering phenomena, and achieve rapid transient response. A novel adaptive fault tolerant Sliding Mode Control (SMC) approach is developed to address the challenges provided by uncertainties and actuator defects in real robotics tasks. Originality. The present work combined the AFT2FTSMC algorithm in order to give robust controllers for trajectory tracking of manipulator’s robot in presence parameters uncertainties, external disturbance, and faults. We use an adaptive fuzzy logic system to estimate the robot’s timevarying, nonlinear, and unfamiliar dynamics. A strong adaptive term is created to counteract actuator defects and approximation errors while also guaranteeing the convergence and stability of the entire robot control system. Novelty. The implemented controller effectively mitigates the chattering problem while maintaining the tracking precision and robustness of the system. The stability analysis has been conducted using the Lyapunov approach. Results. Numerical simulation and capability comparison with other control strategies show the effectiveness of the developed control algorithm. [ABSTRACT FROM AUTHOR]

The task of aircraft motion control has to be solved under conditions of numerous heterogeneous uncertainties both in the aircraft motion model and in the environment in which the aircraft is flying. These uncertainties, in particular, are caused by the fact that in the flight of the aircraft can occur various kinds of abnormal situations caused by failures of equipment and systems of the aircraft, damage to the airframe and propulsion system of the aircraft. Some of these failures and damages have a direct impact on the dynamic characteristics of the aircraft as a control object. In this regard, the problem arises of such an adjustment of aircraft control algorithms that would provide the ability to adapt to the changed dynamics of the aircraft. It is extremely difficult, and in some cases impossible, to foresee in advance all possible damages, failures and their combinations. Hence, it is necessary to implement adaptive flight control algorithms that are able to adjust to the changing situation. One of the effective tools for solving such problems is reinforcement learning in the Approximate Dynamic Programming (ADP) variant, in combination with artificial neural networks. In the last decade, a family of methods known as Adaptive Critic Design (ACD) has been actively developed within the ADP approach to control the behavior of complex dynamic systems. In our paper we consider the application of one of the variants of the ACD approach, namely SNAC (Single Network Adaptive Critic) and its development through its joint use with the method of dynamic inversion. The effectiveness of this approach is demonstrated on the example of longitudinal motion control of a supersonic transport airplane. [ABSTRACT FROM AUTHOR]

The paper considers the problem of a mobile two-wheeled robot control in the task of tracking a given position on the plane. The main idea is based on the use of multi-level decomposition during the synthesis of the control law. A distinctive feature of the considered problem statement is consideration of the actuators dynamic and the influence of external unknown disturbances. Using the synthesized control law, the asymptotic convergence of the robot to the path defined on the plane is ensured. [ABSTRACT FROM AUTHOR]

The problem of synthesizing stabilization laws for lateral motion of a maneuverable aircraft at the lack of data on its sideslip and roll angles is analytically solved. The solution is based on the improved method of output signal control synthesis, which provides the specified spectrum of MIMO-system motion. The results of analytical synthesis of the control law and numerical simulation data are presented. [ABSTRACT FROM AUTHOR]

The design of laws that control the industrial facilities is the basic concerns of engineers in order to ensure the optimal cost-effectiveness of these facilities. In the literature, most of the control laws deal with the linear systems whereas most of the industrial facilities are a nonlinear systems that are difficult to control. In this context falls this paper that deals with the design of a feed backing control law for a class of nonlinear systems. In this paper, a design of a feed backing control law for a class of nonlinear systems is proposed. The synthesis of this control law is inspired by exploiting the duality between the techniques of high gain observer. Besides, it will be shown that the proposed control law can perfectly be robust in the stochastic environment while reducing appropriately the noise control system sensitivity. Finally, the proposed control law will be validated in simulation through a nonlinear system. [ABSTRACT FROM AUTHOR]

The field of civil engineering has witnessed significant development since the emergence of innovative control strategies that enhanced the construction of structures, imparting valuable resistance against dynamic loads like wind or earthquakes. Despite numerous articles highlighting the potential of various control approaches to reduce vibration, their effectiveness in mitigating the dynamic effects on structures under real-world conditions appears limited once implemented. A variety of factors, including practical constraints, the choice of the control system device, the shape of the structure, and the amount of control energy deployed, contribute to this lack of efficiency. Within this context, the literature primarily addressed the discrepancy between the mathematical model and the actual structure model, commonly referred to as parameter uncertainties, in the controller design process. In other words, logical continuity in this field involves the application of a more adapted control approach, which enhances performance by incorporating more practical aspects in the controller synthesis procedure. These aspects include the dynamics of the control device, high-frequency neglected modes, and the inherent limitations or constraints of the control equipment. Thus, this study treats two main active control systems, ABS and AMD. While applying an approach known as μ-synthesis, the robust control was retained because of its ability to include all these considerations when they act simultaneously. We used this control to make sure that a three-degree-of-freedom structure responds as little as possible to seismic requests, which are shown by an uncertain model. We then conducted a comparative study between these two systems, focusing on displacement reduction and control force, while exploring a classic AMD control system at the top of the structure and an ABS control system at the bottom. This approach proved to be a powerful way to deal with the uncertainties affecting the structure and achieve the stability design objectives, given the satisfying simulation results. [ABSTRACT FROM AUTHOR]

In this paper, an interval multiobserver is designed for nonlinear systems subject to unknown but bounded disturbances and measurement noises. The behavior of discrete nonlinear systems is described by an uncoupled multimodel. Linear Matrix Inequalities (LMIs) are formulated to study the stability of the proposed systems and to ensure the cooperativity dynamic of the observation errors. An augmented system is introduced to apply a tracking control where the control gains are obtained by pole placement. Finally, a numerical example is proposed to verify the efficiency of the interval multiobserver in state estimation and to prove the performance of the control strategy to follow the desired trajectory. [ABSTRACT FROM AUTHOR]

This paper presents the design of an ℒ1 adaptive control system for the stabilization of a two-dimensional aeroelastic system with structural nonlinearities and unsteady aerodynamics, using a single trailing-edge control surface. This model describes the plunge and pitch motion of a prototypical wing. It is assumed that its parameters are unknown and external disturbances are present. The unsteady aerodynamics are modeled with an approximation to Theodorsen's theory. The system exhibits limit cycle oscillations beyond a critical speed. Based on the ℒ1 adaptive control theory, a control law is developed for the trajectory control of the integral of the pitch angle. The control system includes a state predictor, a projection algorithm-based adaptation law designed based on the Lyapunov method, and a stabilizing control law. For the synthesis of the control law only the pitch angle and its derivative are measured. Simulation results show that in the closed-loop system, the aeroelastic vibrations are suppressed, despite parametric uncertainties and gust loads. Furthermore the performance limits of this ℒ1 adaptive law with respect to the freestream velocity and strength of gust load are examined. [ABSTRACT FROM AUTHOR]

A tandem queuing system that contains two single-channel stations with finite buffers and allows blocking of the first server is considered. The first station receives nonstationary Poisson packet flow that is processed at a controlled rate. In the case of the queue overflow in the first system, the input packet is lost. The second station does not allow overflow due to control of the acceptance probability (a decrease in such a probability leads to slowing of packet sending from the first station). The queuing system is described with the aid of the controlled Markov process . The optimal control problem is considered over a finite time horizon using the criterion of minimum average losses under the constraints on the total service time and energy consumption of the first station. Optimization algorithms are proposed for synthesis of the control law for nonstationary data flow in two-agent robotic system. [ABSTRACT FROM AUTHOR]

The problem of optimal synthesis of a nonlinear system's control law parameters of satellite attitude control under constraints is considered. The maximum stability degree of a system is considered as an optimality criterion. The reaction wheels' control moments and angular velocities achievable within the drives' physical characteristics are considered as constraints. A linear model of the system converted from the original nonlinear model was used to solve the problem. The decomposition method, based on the transition from real time to relative time, is used to separate the tasks of optimality criterion maximization and constraints consideration. A method of synthesizing the optimal form of system transient process according to the maximum stability degree criterion is developed. An analytical method for determining the optimal values of control law parameters is proposed, based on the structural features of the linear differential equations system. A method that takes into account constraints on control moments and angular velocities of reaction wheels, based on transition scale from relative time to real time and its calculation algorithm, ensuring that conditions of all constraints are met, is developed. An example of solving the problem of optimal system synthesis is considered. The results demonstrate the effectiveness and simplicity of the proposed methods and algorithm for targeted selection of a system's technical characteristics, taking into account constraints on reaction wheels' maximum angular velocities and control moments values. [ABSTRACT FROM AUTHOR]

The research is aimed at creating a methodology for increasing the positioning accuracy of an industrial robot and minimizing the vibration of the robot gripper by applying machine learning based on the developed mathematical model for estimating the positioning error. Two components of positioning accuracy are considered: geometric and kinematic errors and elastic static deformations. The dynamic error in the partial system of motion of the robot manipulator links is analyzed. The equation of partial motions is obtained from Lagrange's differential equation of motion of the II kind. The system of differential equations for the positioning error was solved analytically by Euler's method. An example of modeling the position and orientation error of the gripper due to temperature deformations of the third link for the manipulator scheme is given. An example of the modeling of static deformations and errors of the manipulator with elastic pliability of the robot links is given. An example of dynamic error modeling in a partial system of motion of the robot links is given. The proposed method of modeling robot gripper positioning errors makes it possible to increase the positioning accuracy of the industrial robot and minimize the vibration of the gripper. Having a mathematical model of positioning errors, it is possible to compensate for the positioning error by changing the speed of movement of the gripper reference point before determining the direct kinematic task. [ABSTRACT FROM AUTHOR]

The paper concerns the technology of the design, realization, and testing of a flexible smart wing in a wind tunnel equipped with a turbulence generator. The system of smart wing, described in detail, consists mainly of: a physical model of the wing with an aileron; an electric servomotor of broadband with a connecting rod-crank mechanism for converting the rectilinear motion of the servoactuator into the aileron deflection; two transducers: an encoder for measuring the deflection of the control aileron and an accelerometer mounted on the wing to measure its bending and torsional vibrations; a procedure for determining the mathematical model of the wing by experimental identification; a turbulence generator in the wind tunnel; implemented ℋ ∞ and LQG algorithms for active control of vibrations. The attenuation experimentally obtained for the aeroelastic vibrations of the wing, but also for those accentuated by the turbulence, reaches values of up to 50%. [ABSTRACT FROM AUTHOR]

The paper examines the perspectives of linear-quadratic (LQ) optimal control in steering the process of goods distribution in logistic systems with multiple transportation options. In the considered class, the distribution centre governs the stock replenishment process of subordinate depots, from which un uncertain market demand is served. The centre is linked with the depots via shared supply channels with different characteristics regarding delay, reliability, and capacity, e.g. train vs truck delivery. The design objective is a rule of dynamical channel allocation – how many goods to send in a period using a given mode – so that balanced, cost-efficient system performance and high customer service rate are achieved. The received goods are inspected for quality defects and rejected when faulty. Thus, one needs to cope with two major sources of uncertainty: unpredictable demand variations and channel imperfections. A multi-variable LQ optimal controller is designed and presented in closed form for detailed analytical and numerical treatment. It is formally shown that despite perturbations, the controller always establishes a non-negative and upper-bounded replenishment signal, and the stock level does not cross the reference value. Conditions for warehouse space selection and obtaining full demand satisfaction at the depots are specified and formally proved. [ABSTRACT FROM AUTHOR]

In this work, a new robust controller is proposed for building climate control in presence of parametric uncertainties. The design of the controller is based on the Model Predictive Control (MPC) framework and it includes time-varying constraints. The robust design is implemented by explicitly considering parametric uncertainty in the synthesis of the control law. Variations of the parameters of the buildings are represented in the form of polytopic uncertainty. The robust control action is obtained by minimizing an appropriate 'worst-case' cost function, which leads to the definition of a min–max optimization problem. This optimization problem is formulated using Linear Matrix Inequalities (LMIs) that allow for efficient numerical computation of the control command. Simulation results show that the proposed approach is successful in keeping the indoor temperature of the building in the desired range even in presence of large model uncertainties. The proposed controller is also compared with a nominal controller synthesized without accounting for parametric uncertainty. Numerical results confirm 24% better performance of the robust design in comparison with the nominal controller with same conditions. Further, simulation results also demonstrate that the robust control system achieves 17% better performance in the case of severe conditions of uncertainty. [ABSTRACT FROM AUTHOR]

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This paper presents an observer based dynamic fuzzy logic system (DFLS) scheme for a class of unknown single-input single-output (SISO) nonlinear dynamic systems with external disturbances. The proposed approach does not need the availability of the state variables. Within this scheme, the DFLS is employed to identify the unknown nonlinear dynamic system. The control law and parameter adaptation laws of the DFLS are derived based on Lyapunov synthesis approach. The control law is robustfied in H sense to attenuate external disturbance, model uncertainties, and fuzzy approximation errors. It is shown that under appropriate assumptions, it guarantees the boundedness of all the signals in the closed-loop system and the asymptotic convergence to zero of tracking errors. The proposed method is applied to an inverted pendulum system to verify the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper presents an indirect adaptive fuzzy control scheme for a class of unknown multi-input multi-output (MIMO) nonlinear systems with external disturbances. Within this scheme, the dynamic fuzzy logic system (DFLS) is employed to identify the unknown nonlinear MIMO systems. The control law and parameter adaptation laws of DFLS are derived based on the Lyapunov synthesis approach. The control law is robustified in H∞ sense to attenuate external disturbance, model uncertainties, and fuzzy approximation errors. It is shown that under appropriate assumptions it guarantees the boundness of all signals in the closed-loop system and the asymptotic convergence to zero of tracking errors. An extensive simulation on the tracking control of a two-link rigid robotic manipulator verifies the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]