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This paper investigates the finite-time time-varying formation-containment control problem for satellite formation flying under discontinuous control protocols based on nonsmooth analysis. The desired consequence is that the follower satellites can converge into a dynamic convex hull in finite time, which is spanned by leader satellites' time-varying formation according to the reference signal. Firstly, to accomplish this objective, a finite-time time-varying formation-containment control strategy is proposed for satellite formation system in present of the bounded disturbances and satellites' accelerations, which are known for each satellite. Then, considering the case that the information of disturbances may not be measured accurately and the accelerations of satellites may not be obtained globally in some practice application scenarios, a fully distributed adaptive control strategy is proposed by introducing the dynamic variables. The adaptive variables can compensate the unknown items and adjust with the evolution of neighbour satellites' states, which makes the controller more flexible. Moreover, the proposed control strategies are able to guarantee a fast dynamic response and also a suppression of disturbance. Finally, the performances of the proposed strategies are demonstrated by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper addresses a problem of optimal error quantification in the framework of robust control theory in the 1 setup. The upper bounds of biased external disturbance and the gains of coprime factor perturbations in a discrete-time linear time invariant SISO plant are assumed to be unknown. The computation of optimal data-consistent upper bounds under a known bias of external disturbance has been simplified to linear programming. This allows for the computation of optimal estimates in real-time and their application to achieve optimal robust steady-state tracking even when facing an unknown bias in the external disturbance. The presented results have been illustrated through computer simulations. [ABSTRACT FROM AUTHOR]

Due to the breadth and complexity of spatial motion, and the nonlinear coupling caused by multiple degree-of-freedom, the control difficulties of spatial cooperative multirobot system are two mainly aspects, the modeling method and the dispose of uncertainty. For modeling, the process of directly using ordinary methods such as Lagrange mechanics are very complex. For control, the external disturbances and imperceptible errors will lead to the instability of dynamic system, these factors are collectively referred to as uncertainty. In this paper, a universal modeling method based on spatial cooperative multirobot system was proposed, and an adaptive robust controller was designed to solve the control problems. Simplify the connection link into a load and divide the system into two symmetrical subsystems by disconnecting the load center. The inherent physical position and given trajectories were unified as constraints. The constraints applied on system are creatively converted into consistent standard form through the Udwadia-Kalaba (U-K) method, and the corresponding constraints can be generated easily from the Udwadia-Kalaba basic equations. In addition, a nominal term to stable the system and an adaptive term was added to the controller. The adaptive term works through an adaptive parameter, the parameter estimates the uncertainty bound, thus, only the boundedness of uncertainty should be known, and more accurate control input can be gained. Eventually, the correctness of the model and controller has been confirmed through numerical simulation. [ABSTRACT FROM AUTHOR]

In the structure of the generating capacities of the Integrated Power System of Ukraine, the power units of thermal power plants (TPP) with a capacity of 200 and 300 MW carry the main load to ensure the balance of the daily power demand curve in semi-peak mode. In 2022, these power units were one of the main targets of missile attacks aimed at unbalancing the energy system. The emergency shutdown of some power units must be compensated by the capacity of others, otherwise emergency shutdowns of power supply to consumers are introduced. The issue of increasing the maneuverability of existing power units is extremely acute today. Boiler units of TPP are characterized by changes in dynamic characteristics when their operation mode is changed. That is why control systems are subject to increased requirements for the quality of functioning and stability margins. The article contains an analysis of modern developments in the field of synthesis of robust and adaptive control systems by inertial circuits of TPP boiler units. Control schemes with tabular adjustment of PI controller parameters, piecewise-linear adaptation, as well as schemes with an internal model control and with a dynamic corrector are considered. The water-steam flow path of the pulverized coal direct-flow boiler unit of the TPP with a capacity of 300 MW is considered as a control object. The setting parameters of the considered circuits are calculated according to known methods. Computer models of regulation schemes were built, based on which simulations of their operation were carried out. A comparative analysis of quality indicators of their functioning was carried out. Stability margins of control systems in the entire range of operating loads of the power unit are calculated. Graphs of the dependence of the stability reserves on the gain and on the phase depending on the load of the power unit are constructed. The obtained results are summarized in a final table indicating the advantages and disadvantages of each of the considered schemes. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid offline–online neural identification-based robust adaptive control strategy for quadrotors subject to parameter uncertainties and external disturbances. A new method of using hybrid offline–online neural identification is developed to compensate for the residual force and moment caused by parameter uncertainties. Unlike previous methods that ignore the relevance of uncertainties in the time dimension, the proposed neural identification method mines temporal features of states from historical data by introducing long short-term memory (LSTM) networks, resulting in high identification accuracy. Furthermore, an online adaptation update law is designed to optimize the weights of the network estimates for strong robustness. Consequently, based on the identification of the network, a robust tracking controller on S E (3) is constructed, which is capable of attenuating the bounded disturbances by introducing anti-disturbance components. Finally, numerical simulations and experiments in the real physical world are carried out to verify the performance. The experimental results demonstrate that the proposed strategy not only achieves more accurate uncertainty identification in comparison to the existing methods, but also realizes a 44.28% reduction in the root-mean-square error (RMSE) of the position under the lump uncertainties, which illustrates enhanced robustness and generalizability. Video: https://youtu.be/3kIG5fcQaVE. • A hybrid offline–online neural identification-based control strategy is designed. • LSTM models trained based on meta learning are used to mine temporal correlation. • A hybrid offline–online neural identification method enhances the generalizability. • The proposed controller is robust to parameter uncertainty and external disturbance. • The control performance is evaluated through comparative simulations and experiments. [ABSTRACT FROM AUTHOR]

In this paper, the leader–follower robust synchronization issue is mainly addressed for reaction–diffusion neural networks (RDNNs) with multiple leaders and external disturbances under directed graphs. Based on the σ modification approach, we propose a novel distributed adaptive controller by adding a term − θ i (c i − 1) 2 to avoid the phenomenon of parameter drift, that is, the adaptive parameters grow to infinity. Meanwhile, different from the adaptive control algorithm proposed in the undirected graph, we introduce a new function χ i (t) to provide additional freedom for the design to achieve robust containment when confronted with external disturbances. Further, the robustness of tracking synchronization with one leader is guaranteed by the proposed adaptive controller when the external disturbances concerning L 2 norm are bounded. Finally, relevant numerical simulation graphics are displayed separately to verify the correctness of the related theoretical results. [ABSTRACT FROM AUTHOR]

A differential drive catamaran unmanned surface vehicle tracking control in presence of external disturbances and uncertainties is addressed. A super-twisting control considering a single adaptive gain is adopted, where the number of tuning parameters of this control gain is reduced compared with standard adaptive super-twisting approaches. Furthermore, the gain exhibits smooth dynamics compared with controls using discontinuous functions signals. An analysis of the closed loop stability is provided using a Lyapunov approach. The proposed adaptive super-twisting approach is designed to drive the vessel along time-varying trajectories in presence of perturbations, ensuring robustness, and practical finite-time convergence. Numerical simulations, and real-time experimental tests using a prototype, illustrate the control performance under payload uncertainty and external perturbations. For further demonstration, a comparison with some of the existing versions of the super-twisting control included one with variable gain is provided. [ABSTRACT FROM AUTHOR]

This article deals with the distributed $\mathcal {H}_{\infty }$ robust control problem for linear multiagent systems perturbed by external disturbances and norm-bounded uncertain parameters over the Markovian randomly switching communication topologies. To tackle this problem, the distributed observer-based controller is proposed, which requires the relative information between neighbors and the absolute information of a subset of the nodes, and thus is intrinsically distributed. It is of great interest to see that the distributed $\mathcal {H}_{\infty }$ robust control problem governed by such a controller can be converted to the stabilization with $\mathcal {H}_{\infty }$ disturbance attenuation problems of some decoupled linear systems, whose dimensions equal those of a single node. Then, the $\mathcal {H}_{\infty }$ stochastic robust performance region is defined to indicate the robustness of this controller against the variation of communication topologies. It is theoretically shown that the distributed observer-based controller yields bounded and connected robust performance region. Finally, the theoretical results are verified by conducting numerical simulations and experiments. [ABSTRACT FROM AUTHOR]

This paper mainly focuses on the cooperative robust consensus tracking problem of uncertain networked Euler-Lagrange systems (NELSs) with time-varying delays and output constraints. By systematically integrating the neural network (NN) adaptive technique and the logarithmic type Barrier Lyapunov Function (BLF) in combination with the additional robust control law, two distributed robust consensus schemes for uncertain NELSs are proposed for two cases of time-varying communication and input delays respectively, which can fully guarantee to constrain the output consensus error within a safety region simultaneously. Furthermore, numerical simulation examples are provided to demonstrate the comparable potential advantages of the proposed robust control law over some existing algorithms, including adaptability, stability, and robustness, as well as delay effects. • An NN-based robust controller is designed to effectively handle the uncertainty of NELSs. • Combining NN with BLF ensures the adaptability, stability, and robustness of the consensus tracking scheme for NELSs. • A unified analytical framework is developed by deriving upper bounds on the allowed values of communication and input delays. [ABSTRACT FROM AUTHOR]

The problem of decentralised robust tracking and model following is investigated for a class of uncertain large-scale interconnected systems with both any time-varying delays and any dead-zone input constraints. By combining an adaptive approach with a multiply integral inequality proposed recently in the control literature, a new design method is developed so that (i) the designed decentralised robust tracking control schemes are direct, i.e. not the complicated ones composed of two parts, which can overwhelm the dead-zone input constraints; (ii) it is unnecessary to know any information on the characteristic parameters of dead-zone functions and the time-varying delays, which makes the decentralised robust tracking control rather simple. It is also proved that the local tracking error between the output of each actual subsystem with delays and input constraints and the dynamical signals of the corresponding local reference model is uniformly exponentially bounded. Finally, a numerical example is also given to describe the design procedure and the simulations of this numerical example are implemented to demonstrate the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive robust boundary controller is designed for an unstable heat equation with external disturbance flowing into the control end. The disturbance and uncertainty effect is cancelled out in the closed-loop system by using on-line approximation of disturbance upper-bound provided as an output of adaptive robust update law. The asymptotic stability of the controlled system in the presence of unknown disturbance and/or parametric uncertainties is proved utilising the Lyapunov theorem. Unlike previous researches, the control implementation does not require prior knowledge of unknown disturbance. Moreover, the controller does not require measuring the system states or estimating the system states by an observer. The adaptive robust controller can be regarded as a combination of the best qualities of the adaptive controller and the robust controller with no prior knowledge of system uncertainty, and asymptotic tracking error performance. Numerical simulations and comparisons are provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

We consider adaptive optimal tracking problems for a minimum-phase discrete-time plant with uncertainty in the output channel and bounded exogenous disturbance. The coefficients of the equation of the linear time-invariant nominal model, the uncertainty gain, and the upper bound of the exogenous disturbance are assumed to be unknown, and the worst-case asymptotic tracking error serves as the performance criterion. It is shown that the statement of the optimal problem depends on a priori information about the bounded control. The solution of the problems is based on the polyhedral estimation of all unknown parameters and the use of the performance factor of the tracking problem as an identification criterion for calculating the current optimal estimates. The performance and efficiency of the proposed control algorithms is illustrated by the results of numerical simulation. [ABSTRACT FROM AUTHOR]

This paper proposes a method to prevent overlearning (weight drift) and bursting in adaptive control using the cerebellar model arithmetic computer (CMAC). Traditional robust adaptive methods such as deadzone, projection, e-modification are not necessarily suitable for CMAC control. The proposed method relies on the idea of weight smoothing, where the difference between adjacent weights in the CMAC is penalized in the adaptation. Previously proposed weight smoothing schemes are only suitable for one or two-input CMACs and do not have stability guarantees. This work extends the method for use with n-input CMACs and develops the adaptive scheme within a Lyapunov framework to guarantee uniformly ultimately bounded signals. Simulations with a two-link, flexible-joint robot subject to sinusoidal disturbance demonstrate the performance and stability of the new method. [ABSTRACT FROM AUTHOR]

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Summary: For the high precise tracking control purpose of a cable‐driven manipulator under lumped uncertainties, a novel adaptive fractional‐order nonsingular terminal sliding mode control scheme based on time delay estimation (TDE) is proposed and investigated in this paper. The proposed control scheme mainly has three elements, ie, a TDE element applied to properly compensate the lumped unknown dynamics of the system resulting in a fascinating model‐free feature; a fractional‐order nonsingular terminal sliding mode (FONTSM) surface element used to ensure high precision in the steady phase; and a combined reaching law with adaptive technique adopted to obtain fast convergence and high precision and chatter reduction under complex lumped disturbance. Stability of the closed‐loop control system is analyzed with the Lyapunov stability theory. Comparative simulations and experiments were performed to demonstrate the effectiveness of our proposed control scheme using 2‐DOF (degree of freedom) of a cable‐driven manipulator named Polaris‐I. Corresponding results show that our proposed method can ensure faster convergence, higher precision, and better robustness against complex lumped disturbance than the existing TDE‐based FONTSM and continuous FONTSM control schemes. [ABSTRACT FROM AUTHOR]

This paper presents an aerodynamic model-based robust adaptive control algorithm for close formation flight. The leader aircraft is assumed to be at level and straight flight which characterizes the most common scenario for close formation flight. The formation aerodynamic effects are assumed to be unknown, but an online formation aerodynamic model is available to predict those effects. In light of the online formation aerodynamic model, a robust adaptive control algorithm is thereafter developed on the follower aircraft to counteract the unknown formation aerodynamic effects and obtain highly accurate formation tracking performance. The proposed control algorithm is composed of a baseline controller and an integrator-augmented robust adaptive controller, which can efficiently deal with both matched and mismatched formation aerodynamic effects and external disturbances. The major advantage of the proposed design is that it can achieve at least ultimate bounded tracking control with certain transient performance guaranty. The efficiency and robustness of the proposed control design are eventually validated via numerical simulations of close formation flight at two different scenarios. [ABSTRACT FROM AUTHOR]

In this paper an adaptive fuzzy variable structure control integrated with a proportional plus derivative control is proposed as a robust solution to the trajectory tracking control problem for a differential wheeled mobile robot under effect of uncertainties and disturbances. To minimize the problems found in practical implementations of the classical variable structure controllers, a single-input single-output adaptive fuzzy logic system replaces the discontinuous portion of the controller. Stability analysis and the convergence of tracking errors considering the adaptive law are guaranteed with basis on the Lyapunov theory. Simulation and experimental results of the proposed control strategy are explored. [ABSTRACT FROM AUTHOR]

In this paper, we propose two adaptive control schemes to solve the output tracking control problem of a class of uncertain switched nonlinear systems. The first is a robust scheme constructed based on common Lyapunov function method, aiming to achieve the insensitivity of closed-loop system to parameter switches by estimating the bound on switching parameters. It is analyzed that the system stability under arbitrary switching is established with such a scheme, but the control input required may be relatively large since the estimate of the bound on switching parameters is utilized. To avoid this, we further propose a direct adaptive control scheme by estimating the switching parameters directly, and derive a dwell-time condition for parameter switches based on an extended multiple Lyapunov functions method newly developed, such that the global boundedness of all the closed-loop signals and the convergence of tracking error to a residual around zero are ensured. The effectiveness of the proposed control schemes is illustrated through simulation studies. [ABSTRACT FROM AUTHOR]

In this paper, a new robust adaptive controller is investigated to force an underactuated surface marine vessel to follow a predefined parameterised path at a desired speed, despite actuator saturation and the presence of model uncertainties as well as environmental disturbances induced by waves, wind and sea-currents. To ensure robustness of the path-following controller, time-varying constraint on the off-track error (i.e. the maximal distance from the ship to the reference path) is considered. To address the off-track error constraint the tan-barrier Lyapunov function is incorporated with the control scheme, where the idea of auxiliary design system introduced in Chen, Sam, and Ren (2011) is adopted and its states are used in combination with backstepping and Lyapunov synthesis to adaptive tracking control design with guaranteed stability. Furthermore, the command filters are adopted to implement physical constraints on the virtual control laws so that analytic differentiation of the virtual control laws is avoided. We show that the proposed robust adaptive control law is able to guarantee semi-global uniform ultimate bounded stability of the closed-loop system. Numerical simulations and experimental results are carried out to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Trust management is one of the most challenging issues for the highly heterogeneous Internet of Things (IoT). In the context of the IoT, it is difficult to evaluate the node's trustworthiness in the same trust model when a node provides different services. Guaranteeing the availability of the trust management service is another significant challenge because of the dynamic nature of IoT environments. With these issues in mind, this paper propose a robust and adaptive trust management system for the IoT that is able to measure the trustworthiness of nodes based on feedbacks collected from participants in a specific context and ensure the availability of trust management services. The main contributions of our system are: 1) Proposing a partly decentralized trust management framework, which improves the resiliency of the trust mechanism; 2) Proposing an adaptive trust evaluation scheme and a three-dimensional context representation makes trust evaluation more accurate and specific; 3) Enhancing the adaptive trust evaluation scheme by incorporating a bad behavior factor in trust estimation, which efficiently distinguishes misleading feedbacks from On-Off attacks. Simulation results show the good performance of the proposed system and especially show effectiveness against On-Off attacks compared to other trust mechanisms. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the problem of formation control is considered for a class of unknown nonaffine nonlinear multiagent systems under a repeatable operation environment. To achieve the formation objective, the unknown nonlinear agent's dynamic is first transformed into a compact form dynamic linearization model along the iteration axis. Then, a distributed model‐free adaptive iterative learning control scheme is designed to ensure that all agents can keep their desired deviations from the reference trajectory over the whole time interval. The main results are given for the multiagent systems with fixed communication topologies and the extension to the switching topologies case is also discussed. The feature of this design is that formation control can be solved only depending on the input/output data of each agent. An example is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper introduces an adaptive control method for finite-time modified function projective lag synchronization of uncertain hyperchaotic systems. Based upon novel nonsingular terminal sliding mode surfaces and the adaptive super-twisting algorithm, a controller is proposed to provide robustness, high precision and fast and finite-time modified function projective lag synchronization without the knowledge of the upper bound of uncertainties and unknown external disturbances. In addition, chattering is significantly attenuated due to the inherited continuity of the proposed controller. The global stability and finite-time convergence are rigorously proven. Numerical simulation is presented to demonstrate the effectiveness and feasibility of the proposed strategy and to verify the theoretical results. [ABSTRACT FROM AUTHOR]

The sliding mode control (SMC) strategy is employed to a permanent magnet synchronous motor (PMSM) vector control system in this study to improve system robustness against parameter variations and load disturbance. To decrease the intrinsic chattering behavior of SMC, a speed SMC with an adaptive law and an extended state observer (ESO) is proposed. In this method, based on the Lyapunov stability theorem, adaptive estimation laws are deduced to estimate uncertainties of a PMSM caused by parameter variations and unmodeled dynamics. Online estimated uncertainties can be used to eliminate the effect caused by the real uncertainties. In addition, an ESO is applied to observe the load disturbance in real time. The load disturbance observed value is then utilized to the output side of the speed adaptive SMC controller as feed-forward compensation. Both the simulation and experiment results demonstrate that the proposed approach effectively alleviates system chattering and enhances system robustness against uncertainty and load disturbance. [ABSTRACT FROM AUTHOR]

Rotor speed control of wind turbines is a key factor in achieving the maximum power of wind. It is known that a high-performance controller can significantly increase the amount of energy that can be captured from this source. The main problem regarding this issue is the lack of information about the correct dynamic model of the system. This uncertainty of the model is generally associated with unknown parameters (structured uncertainty) and/or external disturbances (unstructured uncertainty). Some adaptive and robust control approaches are developed in the literature in order to deal respectively with structured and unstructured uncertainties. In this paper, to compensate for both types of uncertainty, a robust controller, which includes an adaptive feedforward term, is proposed to track the optimal speed. In addition to considering the uncertainties, another advantage of the presented approach is that, using a smooth control effort, it provides global asymptotic tracking. A complete stability proof of the system is presented, and simulation results illustrate the effectiveness of the controller. [ABSTRACT FROM AUTHOR]

A neural network robust control is proposed for a class of generic hypersonic flight vehicles with uncertain dynamics and stochastic disturbance. Compared with the present schemes of dealing with dynamic uncertainties and stochastic disturbance, the outstanding feature of the proposed scheme is that only one parameter needs to be estimated at each design step, so that the computational burden can be greatly reduced and the designed controller is much simpler. Moreover, by introducing a performance function in controller design, the prespecified transient and performance of tracking error can be guaranteed. It is proved that all signals of closed-loop system are uniformly ultimately bounded. The simulation results are carried out to illustrate effectiveness of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

The present paper investigates stochastic modelling and a new nonlinear reliable tracking control method for a rehabilitative training walker. The stochastic model is constructed by considering random parameters. A new nonlinear tracking method against actuator fault is proposed based on redundant degree of freedom and a state feedback controller is designed by exploiting an adaptive control technique. It is proved that the mean square of the trajectory tracking error can be made arbitrarily small by choosing appropriate design parameters. As an application, simulation results confirm the effectiveness of the proposed method and verify that the walker with random parameters can provide safe sequential motion when one wheel actuator is at fault. [ABSTRACT FROM AUTHOR]

A Fault Tolerant Attitude Control algorithm for the spacecraft using Single Gimbal Control Moment Gyros (SGCMGs) as actuator is proposed. The controller is designed using the sliding mode control theory to control the gimbal rate directly and there is no singular point in the control algorithm, which means that we don't need to design the steering laws again and the singularity problems can be avoided. Also the gimbal rate saturation is considered when designing the control method. The adaptive control algorithm is used to estimate the disturbance and the boundary of the fault and saturation, which means that no prior information of the fault is needed. Although the controller is designed based on the SGCMGs, it can also be employed when reaction wheels work as the actuator of the spacecraft. Also the complete failure of several SGCMGs is allowed. It is proved based on the Lyapunov stability theorem that the designed control algorithm can achieve the attitude asymptotic stability both on the fault or fault-free condition. The simulation results show that the proposed method has a strong robustness. [ABSTRACT FROM AUTHOR]

This paper proposes, for a class of uncertain nonlinear systems, an adaptive controller based on adaptive second-order sliding mode control and integral sliding mode control concepts. The adaptation strategy solves the problem of gain tuning and has the advantage of chattering reduction. Moreover, limited information about perturbation and uncertainties has to be known. The control is composed of two parts: an adaptive one whose objective is to reject the perturbation and system uncertainties, whereas the second one is chosen such as the nominal part of the system is stabilised in zero. To illustrate the effectiveness of the proposed approach, an application on an academic example is shown with simulation results. [ABSTRACT FROM AUTHOR]

Genetic algorithm is a global probability search algorithm developed by simulating the biological natural selection and genetic evolution mechanism and it has excellent global search ability, however, in practical applications, premature convergence occurs easily in the genetic algorithm. This paper proposes an self-adaptive multi-peak immune genetic algorithm (SMIGA) and this algorithm integrates immunity thought in the biology immune system into the evolutionary process of genetic algorithm, uses selfadaptive dynamic vaccination and provides a downtime criterion, the selection strategy of immune vaccine and the construction method of immune operators so as to promote the population develop towards the optimization trend and suppress the degeneracy phenomenon in the optimization by using the feature information in a selective and purposive manner. The simulation experiment shows that the method of this paper can better solve the optimization problem of multi-peak functions, realize global optimum search, overcome the prematurity problem of the antibody population and improve the effectiveness and robustness of optimization. [ABSTRACT FROM AUTHOR]

This paper studies the fixed-time composite robust tracking control problem of a class of marine surface vessel (MSV) systems with uncertainty items and external disturbances. First, the tracking error is restricted within the bounded range by the tan-type barrier Lyapunov function (TT-BLF). Second, a fixed-time disturbance observer (FTDO) is designed to offset the lumped disturbances caused by system uncertainty items and external disturbances. Then, relying on the characteristics of H ∞ control, the error is limited within the L 2 norm bounded by suppressing the interference of the observation error. Furthermore, considering the importance of saving network resources, an event-triggered controller based on relative thresholds is proposed, which guarantees excellent robustness while greatly reducing the communication bandwidth. Finally, it is shown by Lyapunov stability analysis that all error signals of the nonlinear system converge to a small region close to zero in fixed time under the guidance of the robust control law. The effectiveness of the proposed composite robust controller is verified by numerical simulation results. • A fixed-time observer is employed to offset the lumped disturbances caused by system uncertainty items and external disturbances. • An H∞ control strategy is proposed to improve robustness, which has L 2 gain less than or equal to given γ. • A composite robust controller is proposed to ensure the error signal converge to a small range near zero within a predetermined time and robustness. • A ETS based on relative threshold is developed to greatly reduce the communication bandwidth of the controller. [ABSTRACT FROM AUTHOR]

This paper investigates the control of chaotic systems in the presence of unknown parameters, model uncertainties, and external disturbance. We first discuss the control of a class of chaotic systems and then investigate the control of general chaotic systems. Based on the adaptive control scheme, some novel criteria are proposed via a backstepping-like procedure. As an example, the control of the Zhang hyperchaotic system is investigated via a single input. Some numerical simulations are given to demonstrate the robustness and efficiency of the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper examines attitude tracking problem with unknown actuator dead-zone nonlinearity. A robust adaptive controller with parameter update laws is proposed and analyzed. A smooth inverse of the dead-zone is introduced to compensate for the effect of the dead-zone in controllers design with the adaptive control approach. The dead-zone parameters and the upper bound of the disturbance-like term are estimated by adaptive schemes. The stability of the resulting closed-loop systems is proved by application of Barbalat's Lemma. Numerical simulations are presented to show the effectiveness of the proposed attitude tracking approach. [ABSTRACT FROM AUTHOR]

This paper proposes a backstepping terminal sliding mode control with adaptive algorithm which applied to Quadrotor for free chattering, finite time convergence and robust aims. First of all, dynamic equation of a quadrotor has been obtained based on Euler-Lagrangian equations with considering additional disturbance and uncertainty. Furthermore, a nonlinear control scheme has been proposed to deal against defined perturbations. In the proposed control scheme, instead of using regular control input, the derivative of the control input has been achieved from terminal second-layer sliding surface. An adaptive algorithm has been used to achieve the robust performance against external disturbances like wind effects. The adaptive control law estimates the upper bound of disturbance and uncertainty. Stability and robustness of the proposed controller have been proved by using the classical Lyapunov criterion. The simulation results demonstrate the validation of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Trajectory tracking is a common application method for manipulators. However, the tracking performance is hard to improve if the manipulators contain flexible joints and mismatched uncertainty, especially when the trajectory is nonholonomic. On the basis of the Udwadia–Kalaba Fundamental Equation (UKFE), the prescribed position or velocity trajectories are creatively transformed into second-order standard differential form. The constraint force generated by the trajectories is obtained in closed form with the help of UKFE. Then, a high-order fractional type robust control with an embedded fictitious signal is proposed to achieve practical stability of the system, even if the mismatched uncertainty exists. Only the bound of uncertainty is indispensable, rather than the exact information. A leakage type of adaptive law is proposed to estimate such bound. By introducing a dead-zone, the control will be simplified when the specific parameter enters a certain area. Validity of the proposed controller is verified by numerical simulation with two-link flexible joint manipulator. [ABSTRACT FROM AUTHOR]

Using the interpolation/extrapolation skills of the core function of an iterative adaptive controller, a structurally simple single essential layer neural network-based topological structure is suggested with fast and explicit single-step teaching and data-retrieving abilities. Its operation does not assume massive parallelism, therefore it easily can be simulated by simple sequential program codes not needing sophisticated data synchronization mechanisms. It seems to be advantageous in approximate model-based common, robust, or adaptive controllers that can compensate for the effects of minor modeling imprecisions. In this structure a neuron can be in either a firing or a passive (i.e., producing zero output) state. In firing state its activation function realizes an abstract rotation that maps the desired kinematic data into the space of the necessary control forces. The activation function allows the use of a simple and fast incremental model modification for slowly varying dynamic models. Its operation is exemplified by numerical simulations for a van der Pol oscillator in free motion, and within a Computed Torque type control. To reveal the possibility for efficient model correction, a robust Variable Structure/Sliding Mode Controller is applied, too. The novel structure can be obtained by approximate experimental observations as e.g., the fuzzy models. [ABSTRACT FROM AUTHOR]

The formation control problem for multi-agent systems has been explored in recent years. However, controlling a formation of multiple aerial vehicles in the presence of disturbances has been a challenge for control researchers. To deal with this issue, a robust adaptive formation control algorithm for a group of multiple quadcopters is proposed. A nonlinear model of the dynamics of the formation error is obtained based on a leader–follower scheme. This model considers both the relative position in the x – y plane and the relative heading angle between vehicles in the presence of uncertainties. In addition, by means of a model reference control approach, a robust adaptive formation controller is used to steer the vehicles into a formation pattern and have them maintain the formation shape. Numerical simulations demonstrate the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]