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Radial Basis Function Neural Networks (RBFNN) methods have gained incredible efficiency and applicability in control. This paper presents a nested control strategy for robust trajectory tracking of a quadrotor using adaptive RBF compensation and NN-supervised control embedded with Integrator BackStepping (IBS). The approach addresses the robustness in the presence of modeling uncertainties, sensing noise, and bounded disturbances. The control design is derived from the decentralized inverse dynamics, using adaptive RBFNN for outer-loop disturbance approximation and compensation. In conjunction with an Inner-loop supervised control that stabilizes the quadrotor attitude, preventing initial instability during NN convergence. In addition, an adaptive Extended Kalman Filter (EKF) attenuates noisy signals. Simulation results demonstrate strong adaptability to changes in model parameters, and superior performance when compared to Proportional Integral Derivative (PID), Integrator BackStepping (IBS), and offline decentralized Multi-Layer Perceptron (MLP) algorithms, in terms of parameter convergence, disturbance compensation control, and noise attenuation. [ABSTRACT FROM AUTHOR]

In this paper, the trajectory tracking control problem for underactuated autonomous vehicles moving in 2-D space is studied. Firstly, the trajectory tracking error dynamics with the equivalent point being the origin are given. Since both model and input uncertainties of vehicles are considered, a robust control problem is formulated by giving the extended trajectory tracking error dynamics. Through showing that a robust control law is equivalent to an optimal control law for a nominal system under some conditions, the robust control problem is transformed into an equivalent optimal control problem and a cost function composed of uncertainty bounds and discount factor is constructed. In order to solve the optimal control problem, a policy iteration-based ADP algorithm is proposed, in which two neural networks, called critic and actor networks, are applied respectively to describe the unknown value function and control law. The weights of the two networks are tuned through the gradient descent method at each iteration and the optimality and convergence properties are provided in the sequel. At last, simulation results are given to illustrate the validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The paper presents a robust adaptive control strategy to attain consensus of a specific group of nonlinear and disturbed multi-agent systems during a predefined-time. To address the impacts of nonlinear dynamics and disturbances, adaptive schemes are developed to assess the state-dependent rates and constant boundaries of disturbances and nonlinearities immediately. Relying on the adaptive updated information, a disturbance rejection consensus controller is proposed to synchronize consensus errors within the defined error model, so that the errors can tend to zero within predefined time impacted by nonlinearities and disturbances. The efficacy and validity of the proposed approach is substantiated by the comparative simulation results obtained from a system comprising Chua's circuits. [ABSTRACT FROM AUTHOR]

In this paper, a class of interconnected systems is considered, where the nominal isolated subsystems are fully nonlinear and non-minimum phase. A decentralized Extended Kalman Filter-Extended High Gain Observer (EKF-EHGO) is designed to observe the system states. Then, a systematic backstepping design procedure is employed to develop a novel decentralized robust adaptive output feedback control, in which the adaptive law is designed to counter the effects of the interconnections and uncertainties. The proposed decentralized dynamic output feedback control scheme can guarantee that all the signals in the closed-loop system are uniformly ultimately bounded (UUB). Both interconnections and uncertainties are allowed to be unmatched and bounded by an unknown high-order polynomial, which is a more general form when compared with existing work. Two MATLAB simulation examples are used to demonstrate the effectiveness of the proposed method including a system comprising translational oscillator with rotating actuator (TORA) sub-systems. [ABSTRACT FROM AUTHOR]

Designing highly accurate and robust controls for quantum unitary operations is vital for practical quantum computation. In this paper, we demonstrate that the robustness of quantum gate controls can be enhanced by optimizing the sampling-based infidelity variance, which is formulated as a multi-objective optimization task to achieve high robustness while maintaining high gate fidelity. A two-step approach that first optimizes the average fidelity and then turns to the infidelity variance is proposed, where two modified differential evolution (DE) algorithms, i.e., mixed-guided-strategy DE (MGSDE) and multi-objective mixed-strategy DE (MOMSDE), are designed to search fields for the two steps of robust quantum gate control, respectively. Both MGSDE and MOMSDE adopt the mixed strategy, and in particular, MGSDE adopts a guided mutation scheme to accelerate the convergence, and MOMSDE uses an optimal buffer to explore the Pareto front. Numerical results demonstrate that the proposed approach enhances the control robustness and provides an efficient in-situ learning paradigm to tackle the disturbance problem for the control design of quantum gates. [ABSTRACT FROM AUTHOR]

Relative degree (RD) approach is a powerful tool for obtaining system's input-output dynamics used for output tracking controller designs of minimum phase systems. Designs using the RD alone can fail due both to insufficient control authority in minimum phase systems, and instability of internal/zero dynamics attributed to nonminimum phase systems. A novel definition and a concept of Practical Generalized RD (PGRD) are proposed in this paper and are used in concert with Sliding Mode Control (SMC) to compensate for system perturbations in minimum phase systems. The use of known Generalized Relative Degree (GRD) in nonminimum phase systems allows for the elimination of internal dynamics. However, instability that emerges in the corresponding control dynamic extension is defeating any output tracking controller design. A novel methodology of using GRD for designing continuous SMC in nonminimum phase systems is presented. An algorithm for generating a bounded solution of the unstable dynamic extension is proposed and used in concert with SMC, allowing robust control design for nonminimum phase systems. The efficacy of the proposed GRD-based approaches is demonstrated on a minimum and nonminimum phase rocket attitude control problem both analytically and via simulation. [ABSTRACT FROM AUTHOR]

This paper studies the coverage control problem of unicycle mobile robot network with external disturbance in the dynamic environment. The environment model is described by a time-varying density function, which is not known by the robot network. An observation method is proposed to approximate the unknown density function. It is proved that the density approximated by the robot network converge to the real density and the consensus of coefficient vector is realized in the robot network. Based on the approximated density function, a robust coverage control is successfully designed to drive the unicycle robot network to the optimal configuration and the coverage of the task region is optimized. Finally, the effectiveness of observation method and robust control are shown by simulation results. [ABSTRACT FROM AUTHOR]

Networked systems using redundant channels to transmit data can effectively reduce the probability of data loss and improve system reliability and control margin. However, the structural complexity and economic cost of the system are also increased. To balance the redundancy and feasibility, the ratio of attraction domain to packet loss rate is defined as a balanced feasibility index. In this paper, single-channel packet loss is considered as Bernoulli distribution and a bounded packet loss network system control model is constructed as the arbitrary bounded packet loss control problem for redundant channel transmission network system. Therefore, the robust conditions of the closed-loop system and the constraints of the input and state are established under the framework of robust predictive control to construct the linear matrix inequality (LMI) optimization problem. Finally, to verify the effectiveness of the design method proposed in this paper, the discrete time-varying linear system and the main steam control system with redundant channels are used as study cases. [ABSTRACT FROM AUTHOR]

This paper deals with optimal control strategies robustified by a decoupling super-twisting sliding mode control (ST-SMC) for permanent magnet synchronous machines (PMSM). In general, ST-SMC is a robust method for controlling systems and guarantees asymptotic convergence in cases where the upper bound of model uncertainties such as disturbances and parametric uncertainties is not known a priori, if the upper bound of the derivative is known. The proposed optimal control strategy is designed for a constant torque reference whose control is implemented in two control regions: maximum torque per ampere (MTPA) and flux-weakening control. In the proposed analysis, the operating point of the motor can also be in the saturation region, which makes the estimation of L d and L q in the proposed optimization procedure of particular interest and also important for the decoupling control implemented with ST-SMC. To compensate for typical parameter variations, adaptive parameter estimation is introduced into the control system using an extended Kalman filter (EKF) in combination with a bivariate polynomial. In order to be able to make an assessment of the control performance of the ST-SMC, a comparison with a conventional PI controller is shown at the end of the paper. Measured results using hardware in the loop (HIL) to validate the results and their detailed discussion and analysis are included. [ABSTRACT FROM AUTHOR]

The integrating characteristics are commonly found in composition control and level control of a distillation column in chemical processes. This paper presents a simple and intuitive robust tuning method of two-degree-of-freedom (2DoF) proportional-integral (PI) controller for integrating processes with dead time. The frequency response model matching approach is utilized with performance and robustness considerations for both regulatory and servo control issues. The regulatory control issue aims at matching the frequency response of the closed-loop system with that of the reference model for disturbance rejection, where the feedback controller parameters are calculated by solving a group of overdetermined algebraic equations subject to a robustness constraint evaluated by the maximum sensitivity. The target of the servo response is to follow a prescribed set-point reference trajectory, with the set-point weighting factor tuned to satisfy a defined tracking performance metric. A curve fitting procedure is utilized to generate analytical tuning rules in terms of the process model parameters and the desired robustness specification. It is shown that, apart from giving more exact achievement of the control system robustness, the tuning rules presented work well for a wider range of process dynamics than the existing methods. Illustrative examples are given to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper has studied the event-triggered robust output regulation for linear systems with non-vanishing measurements. A comprehensive event-triggered mechanism (ETM) is designed to determine the transmission instants of both sampling measurement signals and execution control signals. A kind of hybrid regulator has been proposed, consisting of a hybrid filter, observer, stabilizer, internal model, and compensator. Applying a generalized hold device makes the event-based regulator easy to implement. The proposed regulator and ETM achieve that all the closed-loop signals are bounded, and the regulated errors converge to a constant range, which can be adjusted arbitrarily small. [ABSTRACT FROM AUTHOR]

An adaptive sliding mode-model predictive control for the path following of intelligent unmanned vehicle is given in this paper. On account of excellent performances of the sliding mode structure, this algorithm can not only effectively estimate the uncertainty of the vehicle system to further improve the following accuracy, but minish the amount of calculation in comparision with model predictive control. Then, the following accuracy between the real system and the theoretical model can be compensated by the fractional order coefficient of controller. Therefore, an adaptive fractional order sliding mode-fractional order model predictive control is designed to follow the path of the intelligent unmanned vehicle. Meanwhile, the robust stability and control accuracy of the associated control algorithm are proved. Finally, different paths are designed to verify the theoretical analysis of the control performance in the controllers. [ABSTRACT FROM AUTHOR]

This paper proposes an event-triggered distributed robust optimal control algorithm for nonholonomic mobile agents (NMA) systems with collision avoidance, asymmetrically saturated inputs and external disturbances. By employing the limit cycle principle and developing the adaptive dynamic programming, zero-sum game theory, and an event-triggering mechanism, the algorithm can optimize an H ∞ cost function and relax both the perfect velocity tracking assumption and the persistent excitation condition. First, the graph theory is used to establish the communication configuration, followed by the introduction of the distributed kinematic control for collision avoidance. Second, as a perfect velocity tracking assumption cannot be guaranteed under dynamics changes, input constraints and external disturbances, the distributed optimal robust control algorithm is designed. Third, by developing a new event-triggering mechanism, the burden of computational complexity and communications is reduced. The closed-loop stability and the zeno-behavior exclusion are proven by the Lyapunov theory. Finally, a numerical simulation is conducted with comparison to the sampling period–based control algorithm to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper addresses the control problem of an uncertain system suffering from an exogenous disturbance. A new degree of control freedom is developed to handle the problem based on the equivalent-input-disturbance (EID) approach. The effect of the disturbance and uncertainties is equivalent to that of a fictitious disturbance on the control input channel, which is called an EID. A state observer and an improved EID (IEID) estimator are devised to produce an estimate that is used to compensate for the disturbance and uncertainties in a control law. A second-order low-pass filter is employed in the estimator to provide a way to solve a tradeoff between disturbance rejection and noise suppression. The slope of the Bode magnitude curve at high frequencies is two times larger for the IEID estimator than for a conventional one. This makes the IEID estimator less sensitive to measurement noise and more practical. Sufficient analyses reveal the mechanism of disturbance rejection, uncertainty attenuation, and noise suppression of an IEID-based control system. A theorem is derived to guarantee system stability and a procedure is presented for system design. Simulations and experiments of the position control of a magnetic levitation system are carried out to show the validity of the presented method. [ABSTRACT FROM AUTHOR]

• The limited available communication bandwidth is considered in the networked electro-hydraulic servo system. Specifically, the practical application of the event-triggered scheme in an actual electro-hydraulic servo system is a breakthrough in this paper. • Bandwidth constrained problem, sensor installation restricted problem, matched modeling uncertainties and mismatched disturbances are considered in the controller design. • With the help of the state and disturbance observers, the tracking error can converge well with the measured angle signals only. • To verify the effectiveness of the designed controller, the related comparative experiments are carried out. The results show that theoretical analysis and experimentation are cross verified. [Display omitted] From an interdisciplinary perspective, the event-triggered scheme, the state observer, and the nonlinear disturbance observer are introduced in a robust tracking control to study the networked electro-hydraulic servo system control problems with digital communication challenge, sensor installation restricted problem, matched modeling uncertainties, and mismatched disturbances. Control packets are likely to be delayed or even lost in the networked control system when the communication medium is shared by multiple nodes and the available communication bandwidth is limited. Therefore, it is necessary to save communication resources. To improve the control performance and the efficiency of the network resource utilization, the event-triggered scheme is introduced. Specifically, the practical application of the event-triggered scheme in an actual electro-hydraulic servo system is a breakthrough in this paper. In addition, to obtain the real-time states of the unmeasurable system and compensate for both matched disturbances and external disturbances simultaneously, the state observer and the nonlinear disturbance observer are collaboratively designed. Finally, to evaluate the control performance of the designed controller, the related comparative experiments are carried out in an actual system. The results show that theoretical analysis and experimentation are cross verified. [ABSTRACT FROM AUTHOR]

• This paper addresses the agile attitude maneuver of flexible spacecraft using CMGs, which is a more general actuator installation configuration in practice. • The attitude dynamics are globally developed on the Special Orthogonal Group SO(3), avoiding ambiguities and singularities associated with other attitude representations. • An observer is designed to estimate the modal information, and coupled with an adaptive PD+ controller and an active vibration-suppression controller are able to guarantee stability of the closedloop system, which is able to provide high precision attitude stabilization and active vibrationsuppression during an agile maneuver. • The attitude controller is easier to be implemented in engineering compared with the existing flexible spacecraft attitude controllers. This paper addresses the agile attitude maneuver of flexible spacecraft using control moment gyros without modal information. Here, piezoelectric actuators are employed to actively suppress the vibration of flexible appendages. Both the dynamics and the proposed controller are globally developed on the Special Orthogonal Group SO(3), avoiding ambiguities and singularities associated with other attitude representations. More specifically, an observer is first designed to estimate the modal information of vibration. A robust control law is developed by synthesizing a proportional-derivative (PD) controller, an adaptive sliding mode controller, and an active vibration-suppression controller, which use the information of the estimated structural modes. The stability of the closed-loop system is proved using Lyapunov stability theory. Finally, numerical examples are performed to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper addresses a problem of optimal resource allocation for technology innovation ecosystem. Two layers goal are realized. First, an uncertain dynamical system is constructed with the Lotka–Volterra model for the description of the dynamics of the concerned innovation ecosystem, in which the growth rate and the symbiosis coefficient are specially treated as possibly (fast) time-varying uncertain parameters. Second, an adaptive robust resource allocation strategy is designed to drive the errors between the populations and the desired populations to be uniformly bounded and uniformly ultimately bounded, such that the first layer (basic) goal of resource allocation is achieved. Third, a two-player cooperative game is formulated for the seeking of the optimal control parameters, in which two (static) cost functions and a comprehensive performance index are constructed by performance analysis, and then the optimal control parameters (i.e., the Pareto-optimality) are obtained by minimizing the comprehensive performance index, such that the second layer (further) goal of optimal balance between the control inputs and the system performance is achieved. This work should be the first effort that addresses the optimal resource allocation and control for technology innovation ecosystem through a creative combination of dynamic modeling, control theory and game theory. [ABSTRACT FROM AUTHOR]

This paper introduces the Lebesgue sampling approach to the robust stabilization of Boolean control networks (BCNs) with external disturbances. Given a Lebesgue sampling region and a feedback control, a time aggregated system is obtained via the semi-tensor product method. Then, a new criterion is presented for the robust stabilization of time aggregated system. Furthermore, given a signal of Lebesgue sampling, a sequence of the Lebesgue type robust reachable sets is constructed. Based on these reachable sets, several algorithms are presented to design both Lebesgue sampling region and sampled-data state feedback control for the robust stabilization of BCNs. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-time cooperative control problem for a class of multiple-master/multiple-slave (MMMS) teleoperation systems with external disturbances and internal system uncertainties is addressed. The MMMS teleoperation system has many potential applications due to its obvious structure advantages such as powerful environmental applicability, excellent load capacity, flexible collaboration and so on. Meanwhile, considering a large amount of data transmission, various uncertainties and collaborative coupling among the multiple operators and multiple manipulators, it is challenging to design a control strategy for the MMMS teleoperation system to achieve satisfactory control performance. To solve these issues, a novel robust fixed-time control strategy 15 is proposed for the uncertain MMMS teleoperation system. At first, a new virtual master-slave control framework for the MMMS system is constructed, which enhances the transparency of the system and makes system stability analysis easier. Then, new fixed-time disturbance observers (DOs) are designed separately for the master and the slave sides to accurately estimate the internal uncertainties and external disturbances under a more realistic assumption. Moreover, a new multi-dimension nonsingular sliding mode (SM) surface is presented, on which the states of the system can tend to the desired equilibrium in fixed time not affected by the initial state values. The cooperative control strategy based on the new DO and SM surface can not only ensure the fixed-time stability of the system, but also improve the system robustness to the external disturbances and internal uncertainties. In the end, simulations are performed to prove the validity of the theoretical results. [ABSTRACT FROM AUTHOR]

The present work is of both theoretical and tutorial value. Existing autonomous and non-autonomous paradigms are systematized for prescribed- and predefined-time controllers, and the scaling technique is revised for their analysis and synthesis. The fixed-time output feedback design is further developed in the paper under the paradigm with prescribed settling time upper bound. In the numerical study made for a closed-loop perturbed double integrator, pros and cons of the resulting algorithm are revealed and compared with those of prescribed/predefined-time output feedback. Thus, another contribution of the paper is in the exposition of the implementation feasibility for the different-type prescribed-time controllers. [ABSTRACT FROM AUTHOR]

This paper considers the robust output regulation and output constraints of the flexible wing system, under an output disturbance, distributed disturbances, boundary disturbances and a reference. The measurable outputs are merely the in-domain tracking error and the in-domain displacement perturbed by an unknown output disturbance that is used to define the uncertain output constraint. All the above disturbances and reference are supposed to be from an exosystem with unknown initial values. Under the guideline of internal model principle, a PDE-ODE coupled observer is designed to exponentially estimate the states of the wing system and exosystem, and meanwhile guarantee the robustness to the unknown coefficients of the disturbances, reference and output constraint. Observer-based nonlinear controllers are then proposed for the flexible wing system so that the in-domain tracking error is regulated toward zero. Furthermore, the approximately known endpoint tracking errors are further restrained by the estimation of the constraint. A numerical simulation is used to indicate the effectiveness of the designed observer-based dynamic controls. This paper also presents the advantages over the adaptive control and active disturbance rejection control. • A PDE-ODE coupled observer is designed to exponentially estimate the states of the wing system and exosystem, and further gives the approximate values of the endpoint tracking errors and output constraint. • Observer-based nonlinear controllers are proposed to guarantee the robust ourpur regulation of the in-domain tracking error of the flexible wing system. • The approximately known endpoint tracking errors are further restrained by the estimation of the unknwon constraint, which is further proved to be robust to unknown disturbances and references. [ABSTRACT FROM AUTHOR]

This paper proposes a robust switched model-based predictive controller design for discrete linear systems with state constraints, inputs, and disturbances limited in norm. Modeled via linear matrix inequalities, the online and offline designs of the proposed control aim at minimizing the upper bound of the quadratic performance index for a horizon of infinite prediction associated with the state estimator and the switching rule, seeking to guarantee the robust stability for closed-loop systems. To this end, three theorems are formulated. To demonstrate the effectiveness of the control strategy, a comparative analysis is performed between the performance of the proposed model and a benchmark method. From the results, it is possible to conclude that the proposed method is promising in the scope of control of linear systems subject to switching, being more efficient than the benchmark for the stabilization and control of both numerical examples. [ABSTRACT FROM AUTHOR]

This paper presents an improved composite fuzzy learning control for uncertain electrically-driven robot manipulators with input delay and the external disturbances. In the framework of the backstepping algorithm, fuzzy systems are employed to approximate the unknown terms where the accuracy of fuzzy learning is also considered by defining prediction errors. With the aid of integral technique and the dynamic surface control, a variable is engendered for the system in such a way that the input-delayed robotic system is converted to the non-delayed robotic system. Besides, the command-filtered control is used to cope with the complexity explosion of the backstepping-based design. In order to improve the robust behavior of the control system, the proposed control scheme is equipped with disturbance observers (DOBs). Different from the previous works, the information of the input-delayed, the compensated error surfaces (obtained from the command-filtered approach), the prediction errors and the disturbance estimations (derived from DOBs) are unified to construct the proposed control framework. The stability of the overall system is verified by the Lyapunov theorem. The efficiency of the proposed concept is illustrated using various simulations for an electrically-driven robot manipulator in the presence of uncertainties. [ABSTRACT FROM AUTHOR]

In this paper, a new framework of the robust adaptive neural control for nonlinear switched stochastic systems is established in the presence of external disturbances and system uncertainties. In the existing works, the design of robust adaptive control laws for nonlinear switched systems mainly relies on the average dwell time method, while the design and analysis based on the model-dependent average dwell time (MDADT) method remains a challenge. An improved MDADT method is developed for the first time, which greatly relaxes the requirements of Lyapunov functions of any two subsystems. Benefiting from the improved MDADT, a switched disturbance observer for discontinuous disturbances is proposed, which realizes the real-time gain adjustment. For known and unknown piecewise continuous nonlinear functions, a processing method based on the tracking differentiator and the neural network is proposed, which skillfully guarantees the continuity of the control law. The theoretical proof shows that the semiglobal uniform ultimate boundedness of all closed-loop signals can be guaranteed under switching signals with MDADT property, and simulation results of the longitudinal maneuvering control at high angle of attack are given to further illustrate the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

• A braking-by-wire system based on electromagnetic direct drive valve was proposed. • A novel cascade control algorithm with an adaptive integral robust controller was proposed. • A multi-objective optimization design method of control parameters was proposed. • The novel cascade controller effectively improves the control accuracy and response speed. In order to improve the response speed and control precision of the braking system with parameters uncertainty and nonlinear friction, a braking-by-wire system based on the electromagnetic direct-drive valve and a novel cascade control algorithm was proposed in this paper. An electromagnetic linear actuator directly drives the valve spool and rapidly adjusts the pressure of braking wheel cylinders. A dynamic model of electromagnetic direct-drive valve considering improved LuGre dynamic friction is established. A novel cascade control algorithm with an outside loop pressure fuzzy controller and an inside loop electromagnetic direct-drive valve position controller was proposed. An adaptive integral robust inside loop controller is designed by combining friction compensation adaptive control law, linear feedback, and integral robust control. The uncertainty parameters and the friction state are estimated online. The stability of the cascade controller is proved by the Lyapunov method. Then a multi-objective opitimizemization design method of control parameters is proposed, which combines a multi-objective game theory and a technique for order preference by similarity to ideal solution (TOPSIS) based on entropy weight. The results show that the pressurization time of cascade control is less than 0.09 s under the 15 MPa step target signal. The control precision is improved effectively by the cascade controller under the ARTEMIS condition. [ABSTRACT FROM AUTHOR]

This paper investigates the time-varying output formation tracking problem of heterogeneous multi-agent systems subjected to model uncertainties and external disturbances via adaptive event-triggered mechanism. Firstly, an adaptive distributed event-triggered observer is constructed to acquire the leader's state and a time-varying formation output tracking controller utilizing sliding mode method is proposed to deal with the model uncertainties and external disturbances can be addressed. Secondly, an algorithm is given to claim the design procedures of the event-triggered based controller and asymptotic convergence of the controller is proved based on Lyapunov theory. Thirdly, Zeno-behavior is proved to be excluded strictly. Finally, a numerical example is given to illustrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we develop an adaptive iterative learning approach to investigate the trajectory tracking control issue for a class of two-wheeled mobile robots subject to model uncertainties and unknown disturbances. First, we derive the nonlinear velocity error dynamics. Then a parameterization-based adaptive iterative learning control scheme is adopted to achieve precise tracking, along with logic-based update law for the estimated period and bound of the disturbance. Moreover, the boundness of all the closed-loop signals is rigorously analyzed based on the Lyapunov stability theory to provide the theoretical foundation for the proposed method. The experimental results show the efficacy and viability of our results. [ABSTRACT FROM AUTHOR]

Wide-area control is highly efficacious for maintaining sufficient damping of the low-frequency oscillations in the power system. The Wide-Area Measurement System (WAMS) provides wide-area signals to the control site through a communication channel. Even though the wide-area signal improved the dynamic behavior of the power system, a time delay usually exists during the transmission, which is unavoidable. The damping performance of the power system is degraded due to the time delay. In this paper, synchronized and non-synchronized feedback configurations are considered, and the time delay margin is calculated. The Lyapunov theory is adopted for investigating the synchronous and non-synchronous delay-dependent stability criteria for the power system. A lead–lag and a robust H ∞ wide-area damping controller (WADC) are proposed to measure the delay margin for synchronized and non-synchronized delay feedback. The relationship between the damping performance and the delay margin is established. It is observed that a non-synchronous feedback-based controller can endure a larger time delay variation than a synchronous feedback-based controller. The nonlinear simulation is carried out to verify the effectiveness of the proposed controllers in Kundur's two-area system and the IEEE-39 bus test system. [ABSTRACT FROM AUTHOR]

An optimized robust control method is proposed in this paper to deal with the disturbances of nonlinear factors such as uncertainty in belt conveyor and to realize the speed control of belt conveyor. By controlling the subsystems to track the same desired speed, belt breaks and overlaps caused by varying belt speeds from one section to another are limited. First, a fuzzy model is developed by applying fuzzy set theory to describe uncertainties of belt conveyor such as masses, stiffness, damping and frictions. Second, a robust control is designed for the nominal system and compensating for the uncertainty. With the robust control, the belt conveyor system is proved to be uniformly bounded and uniformly ultimately bounded by the Lyapunov approach. Third, the parameters of controller are optimized based on a non-cooperative game approach. The optimal solution is the Nash equilibrium. Optimal solution allows the controller system to perform better and decrease the cost of control. Finally, by comparing with LQR control and different parameters, the feasibility of robust control and the rationality of the optimal parameters are proven. • A method that can effectively avoid belt breakage and folding failures is proposed. • Uncertainty of belt conveyor is described based on fuzzy set theory. • A robust control that ensures the stability of the system is designed. • Control parameters are optimized based on Nash game theory. [ABSTRACT FROM AUTHOR]

This paper proposes a robust digital sliding mode control design for multi-input linear systems that provides the closed-loop system dynamics of an arbitrary order having a specified feasible spectrum of poles. By appropriate selection of auxiliary outputs according to the controllability indices of the system, the system is decoupled into a set of subsystems. The number of these subsystems is equal to the number of control inputs. The desired dynamic of the considered system is achieved using discrete-time higher order sliding mode, where the discrete-time sliding mode of appropriate order is realized in each subsystem. The robustness is based on the fact that the previous values of the matched disturbances are directly reflected in the present value of the switching variables and it will be enhanced by using an estimator/compensator based on integral of sliding function. This control structure looks like discrete-time super-twisting control. Effectiveness of the proposed control is analyzed and its impact on the control system performances is derived. The proposed control approach is illustrated by simulation examples. [ABSTRACT FROM AUTHOR]

This paper proposes a novel model-free controller, considering the double-lift overhead crane system cannot be accurately modeled and affected by external disturbances. Firstly, to improve the convergence speed of the system states, a time-varying sliding mode surface using a sigmoid-like function is proposed. Then, an adjustable weights radial basis function neural network (AWRBFNN) is introduced to estimate and compensate for the unknown dynamics of the system. This AWRBFNN introduces direct and effective model-free properties, but also brings approximation errors. To estimate the uncertain disturbances and the errors of the neural network, an adaptive uncertainty and disturbance estimator (AUDE) is designed. Furthermore, a fast hyperbolic power reaching law is developed to enhance the robustness while suppressing chattering. Considering that the driving capacity of the actual double-lift overhead crane system and the driving motor torque are limited, an innovative continuous auxiliary system is designed to mitigate the effects of the input saturation while reducing overshoot from synchronization errors. Finally, the stability of the control system is analyzed using the Lyapunov stability theory, and the effectiveness and robustness of the control scheme are verified by simulation. [ABSTRACT FROM AUTHOR]

This paper investigates the supervisory adaptive safety control problem for uncertain nonlinear systems with unmeasurable states. In order to estimate unknown parameters and unmeasurable states, a supervisory observer framework consisting of a multi-observer bank and a supervisor unit, is proposed based on a dividing rectangles (DIRECT) algorithm. Under a desired accuracy, the parameter estimates converge to near the true parameters within finite-time while the estimation error of the system state converges to a small neighborhood near the origin. Also, an observer robust adaptive control barrier function is constructed to ensure safety for uncertain nonlinear systems by guaranteeing controlled invariance of a time-varying auxiliary set. By adjusting some parameters in the DIRECT algorithm, the time-varying auxiliary set approaches the original safe set, which reduces the conservatism generated by the compression of the safe set. Finally, two examples, including an adaptive cruise control system, are given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes an original intelligent robust control method for a kind of aviation electric fuel pump (AEFP) systems, in order to realize on-demand fuel supply for aircraft engines, accurately and robustly. By considering the feature of AEFP, the intelligent robust control method is in a cascaded structure, which combines a novel second order integral sliding mode control (SOISMC) approach with uncertainty and disturbance estimator (UDE) strategy, together with a new multi-objective variable speed grey wolf optimization algorithm (MOVSGWO). To let the current loop of AEFP possess both rapidity and robustness, the SOISMC is presented based on an innovative second order integral sliding mode manifold. To realize that AEFP has strong robustness to both the changing of speed command and the pulsation in fuel pump, UDE is utilized for the speed loop of AEFP. The primary parameters in the intelligent robust controller, namely, UDE-SOISMC controller, are optimized by MOVSGWO. The MOVSGWO is a modified grey wolf optimization algorithm with variable speed by particle swarm optimization. Mismatched uncertainties and disturbances in AEFP can be handled by the proposed robust method. The calculation of instantaneous flow and dynamic torque in AEFP is illustrated. Simulation and experimental results verify the effectiveness of the UDE-SOISMC method. [ABSTRACT FROM AUTHOR]

In this paper, an interval observer-based control problem under the FlexRay protocols is investigated for a class of multirate systems in which the noises are assumed to be unknown but bounded. The FlexRay protocol is employed to schedule the information transfer so as to reduce the communication burden. Based on the FlexRay protocol and the multirate sampling mechanism, a new measurement output representation is established with the help of the lifting technique and the augmentation technique, and then, a sufficient condition is proposed to guarantee the interval observer estimation error dynamics are bounded. In addition, the interval observer gain and the H ∞ controller gain are obtained by solving the linear matrix inequalities, which further ensure the H ∞ performance of the closed-loop system. Finally, a numerical simulation verifies the effectiveness of the FlexRay protocols and interval observer-based controllers. [ABSTRACT FROM AUTHOR]

Flying-wing unmanned aerial vehicles have received extensive attention over the past decade because of their excellent aerodynamic and stealth performance. However, the aeroelastic interaction problems among unsteady aerodynamics, flight dynamics, and structural dynamics, such as the body-freedom flutter, are still open. This paper presents the study of a robust control scheme for active body-freedom flutter suppression of a flexible flying-wing unmanned aerial vehicle. The control objective is to expand the boundary of body-freedom flutter and to enhance the control robustness to external unknown disturbance simultaneously. The paper begins with the modeling procedure of a parameter-varying aeroservoelastic plant for the design of control law. Then, it presents how to synthesize a robust controller so as to suppress the flutter instability for a wide flight range of dynamic pressures. Afterwards, the paper shows how to analyze the flutter stability of the closed-loop system and the robustness of the controller, respectively. The numerical results demonstrate that the proposed robust controller can not only expand the flutter boundary of the unmanned aerial vehicle by 30%, but also exhibit the strong robustness to external disturbance. [ABSTRACT FROM AUTHOR]

• In this paper, double closed-loop framework is proposed with the functions of faults and cyber-attacks detection. • The models of cyber-attacks, denial-of-service, information disclosure (privacy attack), stealthy attack and replay attacks, are formulated to be typical NCS models with parameter uncertainties from control theory perspective. • Information technique (IT) is synthesized together with control theory, and a novel framework is designed based on typical CPS structure, effective attack defense scenarios is devised and applied on this framework to detect and identify the cyber-attacks. In this paper, the issue of CPS security is investigated. By analyzing the process of multi-sources cyber-attacks of denial-of-service (DoS), information disclosure, stealthy attack and replay attack, a unified system model with uncertainties is formulated. Under this system model framework, robust control theory is applied to design the control scenarios for cyber-attack prevention. Furthermore, a double closed-loop NCS framework combined with information integration technology is proposed, necessary conditions for security guarantee are derived. Finally, a DC motor speed moderating example is given to demonstrate the problem. [ABSTRACT FROM AUTHOR]

In this paper, nonlinear control for dealing with a class of uncertain nonlinear systems is discussed according to operator-based coprime factorization method. In detail, firstly, for guaranteeing internal-output stability of nominal nonlinear systems with left factorization, a simple and effective design scheme is proposed with a weak assumption. Simultaneously, based on the proposed scheme, the given nominal nonlinear systems are proved to be coprime. Secondly, tracking performance of the considered systems is obtained by designing a suitable Bezout identity without complicated calculation on the obtained left factorization. Thirdly, with respect to the considered nonlinear system, when it comes to appear perturbation, different adverse effects resulting from different perturbation are considered to guarantee robust stability. For the two different cases, two suffcient conditions using inherent characteristics are proposed for guaranteeing robust stability. Finally, two examples are shown to confirm effectiveness of the proposed design scheme of this paper. [ABSTRACT FROM AUTHOR]

The paper proposes a new robust adaptive control method for a two-link robot manipulator to enhance high tracking control performance despite the presence of dynamic uncertainties and unknown disturbances. The paper examines a Non-Singular Fast Time Sliding Mode (NFTSM) controller based on Wavelet Neural Network (WNN). The Wavelet Network is employed to approximate the upper bound of uncertainties and disturbances. In addition, a compensation term is added to the NFTSM control to attenuate the effect of uncertainties, including unavoidable approximation errors and unknown disturbances. Therefore, to ensure high tracking accuracy, chattering phenomenon reduction, and fast response against approximation errors and uncertainties. The parameters of the controller are tuned online by an adaptive learning algorithm, and online adaptive control laws are determined by the Lyapunov stability theorem. Due to these techniques, the suggested control drives the system to the desired performance where tracking errors converge to zero within a finite time. Simulations performed on a two-link robotic arm demonstrate a higher performance of the proposed adaptive robust NFTSMC based on WNN methodology compared to some advanced control strategies. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of robust H ∞ static output feedback control for a class of uncertain discrete-time switched systems under mode-dependent persistent dwell-time (MPDT) switching scheme. The interested systems are described by the classical polytopic-type uncertain model with time-varying parametric uncertainties. The purpose of this paper is to design a static output feedback controller that ensures the resulting closed-loop system robustly globally uniformly asymptotically stable (GUAS) with a specified H ∞ performance under MPDT switching. By using a quasi-time-dependent (QTD) and parameter-dependent switched Lyapunov-like function suitable to MPDT switching, the sufficient conditions for stability criterion and H ∞ performance analysis are established. Furthermore, a set of QTD switched static output feedback controllers for the polytopic-type uncertain discrete-time switched system with MPDT are first designed. Finally, the effectiveness and potential of the proposed approaches is demonstrated by a water-quality control system. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive fuzzy synergetic controller(AFSC) is designed around a dSpace based experimental setup to provide robust DC–DC buck converter voltage control. Upholding high performance is a challenging task when operating a system under varying operating conditions and parameters uncertainties as is the case when dealing with DC–DC converter control. Fuzzy systems are used to approximate converter dynamics assumed, in this paper, to be unknown (accurate mathematical model is thus considered unavailable). Synergetic control is used to construct a robust continuous control law easy to implement despite varying operating conditions. The combination of these two techniques results in an intelligent robust DC–DC converter control. Unlike many works published, the present paper provides experimental results which corroborate the given analytical stability proof of the closed-loop system and confirm the system signals boundedness. Simulation results followed by experimental validation show that the proposed controller is able to achieve satisfactory voltage regulation performances over system parameters uncertainties, reference output voltage changes, load changes and source voltage variations. [ABSTRACT FROM AUTHOR]

The recent industrial revolution puts competitive requirements on most manufacturing and mechatronic processes. Some of these are economic driven, but most of them have an intrinsic projection on the loop performance achieved in most of closed loops across the various process layers. It turns out that successful operation in a globalization context can only be ensured by robust tuning of controller parameter as an effective way to deal with continuously changing end-user specs and raw product properties. Still, ease of communication in non-specialised process engineering vocabulary must be ensured at all times and ease of implementation on already existing platforms is preferred. Specifications as settling time, overshoot and robustness have a direct meaning in terms of process output and remain most popular amongst process engineers. An intuitive tuning procedure for robustness is based on linear system tools such as frequency response and bandlimited specifications thereof. Loop shaping remains a mature and easy to use methodology, although its tools such as Hinf remain in the shadow of classical PID control for industrial applications. Recently, next to these popular loop shaping methods, new tools have emerged, i.e. fractional order controller tuning rules. The key feature of the latter group is an intrinsic robustness to variations in the gain, time delay and time constant values, hence ideally suited for loop shaping purpose. In this paper, both methods are sketched and discussed in terms of their advantages and disadvantages. A real life control application used in mechatronic applications illustrates the proposed claims. The results support the claim that fractional order controllers outperform in terms of versatility the Hinf control, without losing the generality of conclusions. The paper pleads towards the use of the emerging tools as they are now ready for broader use, while providing the reader with a good perspective of their potential. [ABSTRACT FROM AUTHOR]

• Settling-time and disturbance rejection are primary decisive features for a flight control algorithm of multirotor aircraft. • Existing infinite-time (asymptotic) control methods have a slow convergence rate and less robustness. • Settling-time of finite-time controllers grows unboundedly along with the deviation of ICs from the equilibrium point. • Weighted homogeneity and SMC theories are used to design a robust fixed-time flight controller with explicit upped-bound. • The proposed control approach achieves superior performance compared with recent finite-time/fixed-time controllers. This paper presents a robust scheme for fixed-time tracking control of a multirotor system. The aircraft is subjected to matched lumped disturbances, i.e., unmodeled dynamics, parameters uncertainties, and external perturbations besides measurement noise. Firstly, a novel Nonlinear Homogeneous Continuous Terminal Sliding Manifold (NHCTSM) based on the weighted homogeneity theory is presented. The sliding manifold is designed with prescribed dynamics featuring Global Asymptotic Stability (GAS) and fixed-time convergence. Then, a novel Fixed-time Non-switching Homogeneous Nonsingular Terminal Sliding Mode Control (FNHNTSMC) is proposed for the position and attitude loops by employing the developed NHCTSM and an appropriate reaching law. Moreover, the control framework incorporates a disturbance observer to feedforward and compensate for the disturbances. The designed control scheme can drive the states of the system to the desired references in fixed-time irrespective of the values of the Initial Conditions (ICs). Since the existing works on homogeneous controllers rely on the bi-limit homogeneity concept in the convergence proofs, the estimate of the settling-time or its upper-bound cannot be given explicitly. In contrast, this study employs Lyapunov Quadratic Function (LQF) and Algebraic Lyapunov Equation (ALE) in the stability analysis of both controller and observer. Following this method, an expression of the upper-bound of the settling-time is explicitly derived. Furthermore, to assure the Uniform Ultimate Boundedness (UUB) of all signals in the feedback system, the dynamics of the observer and controller are jointly analyzed. Simulations and experiments are conducted to quantify the control performance. The proposed approach achieves superior performance compared with recent literature on fixed-time/finite-time control and a commercially available PID controller. The comparative results witness that the developed control scheme improves the convergence-time, accuracy, and robustness while overcoming the singularity issue and mitigating the chattering effect of conventional SMC. [ABSTRACT FROM AUTHOR]

• A comprehensive dynamic model of PV power plant has been developed to study small signal stability. • The optimal probabilistically robust P PIλDμ controller is proposed for damping of oscillations. • The NSGA-II is employed to search for PIλDμ controller parameters in the presence of PV connected to single-machine system. • The uncertainty of probabilistically solar irradiation and temperature modeled by Monte Carlo simulation. With the rapidly increasing penetration level of power generated by large scale photovoltaic (PV) units into the power systems, the effect of the variable output power of the PV unit on the stability of the system cannot be ignored. This paper presents a mathematical approach to study the effect of high infiltration of PV power plant on the small signal stability of a power network and design of optimal fractional order PID (PIλDμ) controller for improving the probabilistic small signal stability of the power systems, taking into consideration the uncertainty of system operating conditions. Due to the probabilistic characteristics of large scale PV power generation, deterministic analysis approaches are not able to fully reveal the impact of high-level PV penetration. At first, this work introduces the main module and mathematical modeling of the large scale PV generation jointly with the single-machine infinite-bus power system. In the following, the paper proposes an efficient method that tunes power system stabilizer (PSS) to have the robustness for damping electro-mechanical oscillations in power systems with incorporated random PV power. For this reason, a robust PSS based on hybridization of PIλDμ controller and Non-dominated Sorting Genetic Algorithm (NSGAII) is designed. This paper targets at finding the optimal gain scheduling of the PIλDμ through the use of the advanced heuristic optimization technique with two objective functions in PV-grid connected systems. The performance of the proposed NSGAII-based PIλDμ controller (NSGAII- PIλDμ) under different solar irradiation, temperature conditions and disturbances is tested. Simulation results illustrate that the model presented can be used in designing of essential controllers for large scale PV power plant. [ABSTRACT FROM AUTHOR]

In this paper, we propose less conservative formulations for candidate controllers of robust adaptive mixing control (RAMC) strategies. The RAMCs are employed to solve the trajectory tracking problem throughout the full flight envelope, with guaranteed stability, of a convertible plane (CP) vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV). Initially, the multi-body nonlinear dynamic model of the CP VTOL UAV is obtained using the Euler–Lagrange formalism, from which a linear parameter-varying (LPV) model is derived to be used in the design of the RAMC candidate controllers. The new formulations of the candidate controllers are proposed considering two approaches: a (i) Parallel Distributed Compensation (PDC); and (ii) a parameter-dependent Lyapunov function. Hardware-In-the-Loop (HIL) experiments are performed in a high-fidelity flight simulator to verify the fulfillment of real-time constraints, ensuring a computationally lightweight control strategy ready for implementation in a low-cost embedded computational system. • The multi-body dynamic model of a QuadCP-VTOL UAV which includes aerodynamic effects. • The design of less conservative robust adaptive flight controllers. • The validation of the RAMCs with HIL experiments in a high-fidelity simulator. [ABSTRACT FROM AUTHOR]

This paper proposes a trajectory tracking control strategy for Skid-Steered wheeled UGVs based on a simplified controller design and robust analysis. The position control loops are decoupled by using a virtual orientation angle so that the analysis and design problems can be handled independently as disturbed first-order control systems. The transformed model is useful because it simplifies the robust stability analysis and the definition of the conditions that ensure velocity constraint satisfaction. Furthermore, the proposed analytical control law does not require the solution of any online optimization problem. The usefulness and the design simplicity of the proposed control strategy are illustrated in an experimental case study performed with a Clearpath Husky UGV. • A novel approach for trajectory control of Skid-Steer UGVs has been proposed. • Linear robust design rules are provided for the new analytical control law. • Robust stability and constrains satisfaction can be ensured during navigation. [ABSTRACT FROM AUTHOR]

Real problems in control engineering usually involve many uncertainties and delays. In the search for solutions which deal more adequately with these problems, this paper presents contributions to the theory of the μ -analysis and synthesis applied to uncertain linear fixed time time-delay systems by using Padé approximations. A new necessary and sufficient condition for robust stability for a class of uncertain time-delay systems is presented. From this condition, a novel robust controller synthesis technique is obtained. Furthermore, contributions are presented on the convergence theory of Padé approximations applied to the μ -theory via parametrized optimization technique. In order to better understand the theory presented and verify the effectiveness of the results, examples and comparisons are proposed. Finally, in the conclusions, new lines of research and application are pointed out. [ABSTRACT FROM AUTHOR]

This paper proposes a novel vision-admittance-based adaptive neural network control method for collaborative parallel robots tracking a predefined trajectory and force command. First of all, the vision-admittance model is creatively developed for coupling visual information and force-sensing information in the image feature space and is applied to generate the image feature reference trajectory online according to the desired trajectory and the command of the interaction force. Secondly, considering the system modelling uncertainties and external disturbances, an adaptive Radial basis functions neural network (RBFNN) controller is created to realize high-precision trajectory tracking. The adaptive tuning laws are designed based on the Lyapunov stability theorem so that the entire system's stability and the convergence of the weight adaptation can be guaranteed. Moreover, a sliding mode control (SMC)-based robust compensator is added to the RBFNN controller as an auxiliary term to improve the robustness and stability of the control system. Finally, co-simulations between ADAMS/Simulink are performed on a collaborative Five-bar parallel robot to demonstrate the efficacy of the proposed controller. [ABSTRACT FROM AUTHOR]

Robots are commonly used to perform repetitive or dangerous tasks, and these systems integrate different components that increase the complexity of their dynamic model. Thus, in order to ensure an acceptable tracking performance, the implementation of robust control strategies should be considered. This paper proposes a discrete-time model-free-implementation controller, which relies on the well-known structural properties of mechanical systems, but it does not consider any knowledge on the values of the system parameters. Besides, a fuzzy logic formulation is considered to compensate external disturbances. The outputs of the fuzzy inference system are adapted online to improve the closed-loop response. Finally, representatives simulation and experiments are analyzed to demonstrated the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper is mainly focused on the stabilization problem of uncertain delayed periodic piecewise time-varying systems inclusive of disturbances and faults in actuators. More specifically, the considered system is encompassed of periodic dynamics, which exhibits the nature of switched systems with fixed switching sequence and dwell time. The control protocol is configured in the form of both the present and past state information of the addressed system with passive performance. Moreover, the proposed control approach discloses the stabilization issue mainly by resolving the effect of faults in actuator components. Precisely, the desired periodic gain matrices of the developed controller are calculated by way of solving some matrix inequalities which are derived by making use of Lyapunov stability theory and matrix polynomial approach. As a result, the asymptotic stability of the considered system is ensured in conjunction with satisfied disturbance attenuation index. Conclusively, the simulation results of two numerical examples including mass-spring damping system are presented for validating the theoretical result. [ABSTRACT FROM AUTHOR]

In this paper a novel adaptive robust fault-tolerant sync control method is proposed for a two-slider system where two sliders are constrained by a flexible beam. At first the dynamic models of sync motion system subject to external disturbances and actuator faults are derived. In order to avoid the shortcomings of truncated model, the model of flexible beam is described by using infinite dimensional equation. Then based on the models a novel disturbance observer and an adaptive fault-tolerant control law are designed. The disturbance observer is used to estimate and cancel external disturbances. The adaptive fault-tolerant control is used to deal with the partial loss of effectiveness faults. Lyapunov functional approach is used to prove that the closed-loop system with the proposed control laws is uniformly bounded stable. Finally, some simulation results display that the proposed control laws can obtain excellent sync performance in the present of external disturbances and actuator partial loss of effectiveness faults. [ABSTRACT FROM AUTHOR]