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This paper devotes to the design of all feasible output feedback controllers for the robust output tracking of Boolean control networks with disturbances (DBCNs). First, the output feedback–based robust control invariant set (RCIS) is defined, and a calculation method to find all output feedback–based RCISs of a given set is derived via the truth matrix technique. Second, a class of complete family of robust reachable sets (CFRRSs) is developed; the solvability of robust output tracking problem by output feedback control is verified. Furthermore, a constructive algorithm of all feasible output feedback controllers is presented. Finally, the study of a network about Escherichia coli lactose operon shows the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

Proportional pressure-reducing valve (PPRV) is widely used in brake circuits and pilot supply lines for directional control valves. The performance of PPRV can be degraded because of the effect of magnetic hysteresis, frictions, and other disturbances, which worsens the accuracy of the entire hydraulic system. This paper presents a high-performance pressure controller of a PPRV considering the model nonlinearities. A nonlinear phenomenological model based on the Hammerstein modeling method is first developed to describe the dynamics of a PPRV. A pressure-dependent damping ratio is carried out to handle the asymmetric nonlinearity at the starting process of pressure adjustments, and a series of experiments are conducted to verify the effectiveness of the model. A second-order adaptive robust controller is developed based on the Lyapunov theorem to guarantee the tracking performance in the presence of parameter uncertainties and uncertain nonlinearities. Comparative experiments show that the proposed second-order adaptive robust control algorithm together with the phenomenological model achieves a significant reduction in pressure-tracking error, compared with the one without the proposed plant model, or other existing controllers such as the feedforward proportional–integral–derivative (PID) controller and the first-order adaptive robust controller. [ABSTRACT FROM AUTHOR]

In many engineering problems, modelling the state and output derivative variables in reciprocal state space form can be generated more easily than in standard state space one. The formulation of a robust H ∞ control problem using feedback principle for continuous Lipschitz nonlinear systems with uncertainties in reciprocal state space is presented in this article. In contrast to the existing approaches, the considered model is affected by unknown disturbances, parameter uncertainties and derivative Lipschitz nonlinearities. The asymptotic stability based on the proper Lyapunov functions of the closed-loop system is guaranteed. The H ∞ control design resolution problem is ensured through the linear matrix inequality technique, the lemmas and the use of new variables with S-procedure. The performance of the proposed approach is shown through the experimental results using real-time implementation with a digital signal processing device (DSpace DS 1104). [ABSTRACT FROM AUTHOR]

According to Logvinovich cavity dependent expansion principle, a cavity developed by cavitator has memory effect, which arises cavity deformation at aft part of a supercavitating vehicle and leads time delay of travel state. This delay affects the dynamic behavior through changing hydrodynamic and moment on the control surface, and even induces instability. This paper focuses on the time delay effect of the underwater supercavitating vehicle, and a simplified dynamic model of underwater supercavitating vehicle with delay was established. First, a planing force was simplified in straight level state, then a simplified model of supercavitating vehicle with delay in longitude plane was obtained. Taking depth, pitch angle, vertical speed and pitch rate as state variant, H ∞ state feedback controller was designed by linear matrix inequality (LMI) and Lyapunov stable theory was exploited to prove the asymptotic stability of the system. Simulation results show that, the controlled system is effectiveness for both simplified model and non-simplified model and it can track reference command signal. [ABSTRACT FROM AUTHOR]

Maximum power point tracking (MPPT) controller is the main element in photovoltaic (PV) systems, which is used to ensure maximum power extraction under different meteorological conditions. A MPPT controller can guarantee good performance criteria even in the presence of climatic changes. To achieve this goal, several techniques have been proposed in the literature to improve robustness of the PV system control, such as artificial intelligence and multiswarm particle swarm optimization (MSPSO) algorithm. Previous research on classical MSPSO has shown that the algorithm search behavior cannot find the optimal solution for certain problems. In this context, we investigate the design of a new MPPT controller based on a modified version of heterogeneous multiswarm particle swarm optimization algorithm using an adaptive factor selection strategy (FMSPSO) for PV systems. The proposed FMSPSO can improve the tracking capability with high accuracy, less oscillations, and high robustness. To validate the proposed solution, a simulation and experimental benchmarking of a PV system are presented and analyzed. The obtained results show the effectiveness of the proposed solution compared with the classical MSPSO, fuzzy logic, and perturb and observe (P&O) control presented in other recent works. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for designing a decentralized control law for higher-order systems using the H ∞ complementary sensitivity function (CSF) framework. Higher-order systems often exhibit complex dynamics and interactions between the variables, and hence, sophisticated control strategies are required to attain the desired performance. The proposed method exploits the robustness properties of the H ∞ CSF to achieve effective decentralized control for higher-order systems. The CSF approach focuses on shaping the sensitivity of the system to disturbances, thereby minimizing the impact on system performance. The decentralized nature of the control law allows for independent control of each subsystem, reducing the complexity associated with higher-order systems. Furthermore, the controller parameters are determined graphically by enforcing the H ∞ robust criterion. The effectiveness of the proposed methodology is demonstrated through simulations on higher-order systems from various domains, including process control and other systems. Comparative evaluations against existing control methods highlight the superiority of the H ∞ CSF-based decentralized control law in terms of robustness and performance. [ABSTRACT FROM AUTHOR]

In this paper, a LuGre model–based robust adaptive control (RAC) approach is presented for a pump-controlled hydraulic actuator. We first decompose the LuGre friction model into its steady-state model and a lumped dynamic part applying the mean value theorem, which are compensated by a feedforward term and a robust adaptive term, respectively. The robust adaptive term also plays a part in mismatched disturbance attenuation. In addition, parametric uncertainties and matched disturbances are handled by σ -modified adaptation laws and a robust control law, respectively. The stability of the closed-loop system is proved via the Lyapunov analysis. The efficacy and robustness of the proposed approach are validated by comparative experiments. Compared with common adaptive friction compensation methods, the proposed method has a simpler structure, less computational burden, better control performance, and stronger robustness. Moreover, since the available information is separated from the LuGre model and acts as a model-based compensation term, the design conservativeness of RAC is effectively reduced. [ABSTRACT FROM AUTHOR]

The trajectory tracking control performance of the wheeled mobile robot (WMR) is subject to position constraints, system uncertainties, and external disturbances. This paper explores the mechanism of the position constraints (equality and inequality) and considers the system uncertainties to be time-varying but bounded with fuzzy prescribed bounds. To solve the position constraints and uncertainties problems, a cooperative game-oriented optimal robust control method is proposed to provide high-precision, fast-response performance and robustness for WMR. First, a creative diffeomorphism transformation is proposed to convert the bounded state variables (subject to inequality constraints) into unbounded state variables. Accordingly, a restructured WMR system with the new state variables is established, which is free from inequality constraints. The uncertainties' bound is described as a fuzzy number by employing fuzzy set theory, which builds the fuzzy dynamic system of the WMR. Second, the control goal for this study is to drive the WMR to follow the position constraints despite uncertainties. An optimal robust control is developed to guarantee that the tracking errors of the WMR converge to a predefined neighborhood of origin. Using Lyapunov stability analysis, a fuzzy performance index is constructed, including steady-state performance, time performance, and control effort. The fuzzy performance index is employed as the cost function based on the cooperative game theory. The optimal control design is formulated to seek the Pareto-optimal solution of control parameters. Finally, the stability analysis and comparative experiments demonstrate that the proposed control algorithm can ensure the WMR's superior trajectory tracking convergence performance and strong robustness against uncertainties/disturbances. [ABSTRACT FROM AUTHOR]

The robust stability assessment of the second order plus interval time delay (SOPITD) plant controlled by Fractional-Order Proportional Integral Derivative (FOPID) controllers is the focus of this research. A simple graphical procedure for analyzing the robust stability of the interval system is presented based on the zero exclusion condition and the value set concept. The incorporation of an auxiliary function, derived through a judicious application of fundamental geometric principles intrinsic to convex polygons, serves to significantly alleviate the complexity and facilitate the application of the robust stability analysis approach, thereby affording a more streamlined and efficient means of designing robust control systems. Moreover, the computational burden for the robust stability analysis is also reduced by novel bounds. Moreover, a novel robust performance checking function is provided to improve the performance system. Three illustrative examples are then given to support the findings and show their applicability. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-time sliding mode control scheme is developed to fulfill the trajectory tracking task of a marine surface vehicle with unknown dynamics. To restrain the adverse effects of the unknown dynamics including the parameter inaccuracy and exogenous disturbances, a fixed-time disturbance observer is designed to estimate the lumped uncertainties using the bi-limit homogeneous theory without requiring any knowledge of the model uncertainties. Then, a nominal tracking controller is proposed to stabilize the error dynamic model in the sense of fixed-time Lyapunov stability, based on which a novel integral-type sliding mode manifold with bi-limit homogeneity is constructed to drive tracking error convergence in fixed time. To enhance the robustness of the vessel control system, a disturbance observer–based fixed-time integral sliding mode tracking controller is finally proposed, and the chattering phenomenon is effectively alleviated by direct estimation compensations. The analysis of Lyapunov stability indicates that the closed-loop system is fixed-time stable. Numerical simulations on a model vessel are carried out to validate theoretical results of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This article proposes an efficient adaptive robust control for the eight-pole active magnetic bearing based on a heteropolar structure. Due to the uncertain behavior of active magnetic bearing, the mathematical model of active magnetic bearing is considered to be highly nonlinear and uncertain. As the rotor displacement and velocity are the measurable states, sliding mode control is designed to estimate state variables. Also, a matched disturbance term is used to deal with undesirable disturbances in the active magnetic bearing system. The controller is developed for an active magnetic bearing using the event-triggering-based sliding mode control technique. However, the stability of the proposed scheme has been achieved with the help of Lyapunov theory. Furthermore, the adaptive gain scheduling approach based on a neural network has been augmented to adjust the gain of the proposed controller for active magnetic bearing adaptively. The simulation studies have been performed in detail to demonstrate the use of proposed scheme for the robust control of active magnetic bearings. Finally, a comparative analysis of the proposed control design scheme with a conventional controller has been performed to achieve improved performance satisfying the plant constraints. [ABSTRACT FROM AUTHOR]

Using the Hamiltonian function method with different powers, this paper studies the observer-based finite-time robust control problem of general nonlinear uncertain systems with time delay and presents some new results on this issue. First, by applying Hamiltonian realization method, the paper develops an equivalent Hamiltonian form of original system and designs its observer system. Then, based on the observer system, we study finite-time control problem and present several finite-time stabilization and finite-time robust stabilization results by using the augmented technology and the Lyapunov method. Finally, a real unmanned vehicle is used to verify the performance of the observer-based finite-time robust stabilization controller. Different from the existing literature on Hamiltonian method, the Hamiltonian function in the paper has different powers, which implies that the results developed in the paper have a wider range of application. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of performance tracking and group consensus control of a multiagent system (MAS) under deception attack in the frequency domain. Deception attack, a type of network attack, is modeled and analyzed in a MAS where each agent is a continuous-time system. In contrast to prior works on group consensus, modeling of the attack and its impacts on the MAS are analyzed in the frequency domain. To overcome these effects, an H ∞ robust controller is proposed using the internal stability method. The proposed controller is optimized analytically for H ∞ performance tracking of the MAS and mitigation of deception attack simultaneously. Unlike attacks on communication links, this scheme considers attacks on nodes. The impacts of attacks on the MAS are eliminated without the removal of the compromised nodes. A numerical example demonstrates the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this study, a new fixed-time sliding mode control approach for trajectory tracking control of robotic manipulator systems is devised, which provides fixed-time convergence, robust stabilization, and high precision. A novel fixed-time non-singular fast terminal sliding mode surface (FNFTSMS) with fixed-time convergence is provided, and with settling time independent of the initial condition of the system and can be pre-determined using design parameters. Furthermore, using adaptive disturbance observer and the suggested FNFTSMS, a new composite robust control approach is developed. The adaptive disturbance observer is intended to boost control performance and compensate for unpredictably occurring disturbances. The Lyapunov stability theory is used to establish the fixed-time stability of sliding surface and system states under the suggested composite control strategy. Finally, numerical simulations are carried out using PUMA560 robot in order to demonstrate the effectiveness and efficacy of the proposed control method in terms of accuracy of tracking, fast response, and convergent speed. [ABSTRACT FROM AUTHOR]

Robotic manipulators that utilize the Cable-Pulley based Gravity Compensation Mechanism (CPGCM) have drawn increasing attention due to their exceptional features. In the current study, for the first time, the modeling and control of such systems will be addressed considering the flexibility of the cables. To this end, initially, the dominant dynamics of the cables are identified. Then, the Lagrangian of the whole robotic system including the flexibility of the cables is obtained and the system equations of motion are formed. To design the motion controller for the system, and suppress the vibrations stemmed from the inherent flexibility of the cables, the obtained dynamics is transformed into the standard form of the Singular Perturbation Theory (SPT). To achieve this goal, a combination of the inverse dynamics and Nonsingular Terminal Sliding Mode controller is designed, assuming the rigid model of the cable. A modifying term based on SPT is then added to the previous control signal to tackle the flexibility effects of the cables. The finite-time stability of the overall closed-loop controller is proven using Lyapunov's direct method. The proposed controller is robust to deal with both structured and unstructured uncertainties of the system. The obtained results confirm that the presented robust control algorithm guarantees the stability of the closed-loop system in the finite time. Moreover, it is able to suppress the arisen vibration because of the inherent axial flexibility of the cables in various operational conditions. [ABSTRACT FROM AUTHOR]

Aiming at the problem of payload's swing and communication resource saving of the quadrotor-suspended system under external disturbances, this paper proposes a modeling and control scheme of the quadrotor-suspended system with variable cable length at unequal speed. The inner loop adopts adaptive sliding mode control to enhance the robustness of the system and anti-swing feedforward control to suppress the swing angle, and the outer loop uses improved PD control to track the reference trajectory. Meanwhile, an event-triggered strategy based on dynamic threshold is designed in the inner loop controller, which reduces communication resource occupation. The stability of the coupled nonlinear control system is proved, and the event-triggered strategy can avoid Zeno behavior. Simulation results show that the scheme proposed in this paper can make the quadrotor track the desired trajectory, effectively suppress the payload swing, and save communication resources. [ABSTRACT FROM AUTHOR]

This paper presents the predefined-time convergent robust controller design for a brushed direct current (DC) motor system affected by matched and unmatched deterministic disturbances and stochastic noises, considering both fully measurable and incompletely measurable states. The control algorithm allows the control designer to set the convergence time a priori. The convergence time is independent of initial conditions and disturbances and noises affecting the system. Numerical simulations are conducted to demonstrate efficiency of the designed control algorithm. The obtained results show that the control algorithm counteracts the matched and unmatched disturbances, and noises in case of fully measurable states and mitigates their influence in case of incompletely measurable ones. [ABSTRACT FROM AUTHOR]

This paper proposes a novel integrated path following control scheme for a 4-Wheel Independent Drive (4WID) autonomous vehicle that can adaptively change its mechanism according to the driving conditions. The proposed integrated system handles the lateral steering controller, longitudinal speed, and yaw moment controls considering tire force capacity of each corner. For the lateral controller, the cornering stiffness uncertainties and the transient performance are considered and combined into an H∞ robust controller based on linear matrix inequality (LMI) theory. A super-twisting sliding mode controller (STSMC) based longitudinal controller is designed to deal with disturbances and suppress chattering. When encountering extreme conditions, the active yaw moment controller with hierarchical structure is adaptively activated to prevent large deviation from the reference path and maintain the stability of vehicle. For the tire force allocation, an optimization algorithm is proposed, which has flexible equality constraints to coordinate the longitudinal and lateral motions according to the driving conditions. Simulations based on Carsim-Simulink co-simulation platform show that the proposed method is effective and has excellent performance in both normal and extreme driving conditions. [ABSTRACT FROM AUTHOR]

Robust controllers are attracting considerable interest in control of dynamic systems due to their capability of eliminating parameterized or unparameterized uncertainties. Therefore, model based robust control law is proposed in this study for ride comfort enhancement and applied on a 7 degree-of-freedom full-car suspension system with friction non-linearity. Inertia, spring and damping forces of the system are modelled with parameterized uncertainties while friction forces and external disturbances are considered as unmodelled dynamics, namely, unparameterized uncertainties. To better understand the effectiveness of proposed controller, a dry friction model that has non-linear characteristics is used for analysis. Closed-loop stability of the system is achieved by using well-known Lyapunov Stability Theorem. To better evaluate the effect of proposed robust controller on ride comfort enhancement with successful road holding, extensive numerical analysis is performed and the results are compared with those of previous similar controller and passive suspension system. The effectiveness of proposed control method has been confirmed. Consequently, satisfactory results have been obtained proving that the ride comfort of a vehicle that has both parameterized and unparameterized uncertainties has been further improved with reasonable power consumption values for a vehicle in terms of economic viability. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to handle the trajectory tracking control for a class of three-wheel mobile robot by using a novel adaptive robust control. The mobile robot consists of nonholonomic constraints and uncertainties. The uncertainties include initial condition offset, mass, and moment of inertia of the system, which are time-varying and bounded (unknown). The control force in analytical form is obtained by UK theory, and the adaptive robust control is formulated to handle the uncertainties. For estimating the unknown bounds of uncertainties, the leakage-type adaptive law is designed, which can automatically adjust its own value according to the trajectory tracking errors. Then we verify the uniform boundedness and uniform ultimate boundedness of the proposed control by Lyapunov method. Finally, numerical simulations are conducted to show the trajectory tracking effectiveness of the designed control method. [ABSTRACT FROM AUTHOR]

In this article, an optimal robust constraint-following control is proposed for the underactuated vehicle path tracking problem. First, an underactuated dynamic model is established according to Udwadia–Kalaba (UK) equation, and the system uncertainty is decomposed into matching and mismatching portions based on the system geometric characteristics. The mismatching uncertainty is orthogonal to task space; thus, its influence on system stability is eliminated. Second, the diffeomorphism method is used to creatively set inequality and equality constraints into new equality constraints, and a robust control method for front steering vehicles with parameter-tunable is proposed. Third, an optimal design scheme is proposed for the tunable parameters to minimize the comprehensive index of system performance and control cost. Carsim-Simulink co-simulation shows the effectiveness of the proposed optimal robust control. This article creatively solves the problem of optimal robust control for path tracking of multi-constrained underactuated vehicles. [ABSTRACT FROM AUTHOR]

The control performance of permanent magnet linear synchronous motor (PMLSM) is limited by uncertainty. The uncertainty is bounded by an unknown bound and may be time-varying. The boundary information of uncertainty is unknown but can be described by fuzzy set theory. To mitigate the impact of uncertainty on control performance, this paper proposes a Udwadia–Kalaba theory-based adaptive robust control (UKBARC). The proposed controller contains a Udwadia–Kalaba theory-based controller and an adaptive robust controller. In the Udwadia–Kalaba theory-based controller, the expected trajectory is taken as the expected constraint, and then the control task is converted to make the expected constraint be followed. Additionally, the adaptive robust controller is introduced to handle the system uncertainty without requiring the boundary information of uncertainty. The Lyapunov method is used to show that the performance of uniform boundedness (UB) and uniform ultimate boundedness (UUB) for the PMLSM system is guaranteed. The objective function used to characterize the trade-off between performance and control cost can be derived based on the fuzzy description of uncertainty. Thus, the optimal design of UKBARC (OUKBARC) can be achieved by minimizing the objective function. Simulation and experiment results together verify that high precision motion control can be ensured by using the proposed approach. [ABSTRACT FROM AUTHOR]

To meet the increasing demand for trajectory tracking accuracy and high-efficiency requirements in modern mobile machinery, this paper proposes a practical adaptive robust control method based on the dual-valve parallel electro-hydraulic servo system. Existing tracking control strategies for such servo systems rely on a backstepping method and assume that full states are known, which is stringent in practice. To cope with the problem, we reduce the mathematical model order of the studied system using singular perturbation theory in this paper, and only the position feedback is required for the control implementation. Then, to achieve high accuracy tracking control, a direct adaptive robust control scheme combing with a dynamic flow allocation layer is adopted to synthesize the controller. With this method, parameter uncertainties and load disturbance are rejected, and valve characteristics are considered in the dynamic flow allocation layer to solve the flow redundancy problem, respectively. Convergence of the simplified system tracking results is proved theoretically. Extensive co-simulations and experimental tests are carried out to illustrate the effectiveness of the proposed strategy, both tracking precision and flow distribution can be achieved efficiently by simple parameter adjustments in the field. [ABSTRACT FROM AUTHOR]

Robotic manipulators are nowadays widely used in various underwater scenarios, but their motion control remains a challenging task due to hydrodynamic effects. This article proposes a novel adaptive fuzzy sliding mode control (AFSMC) strategy for precise and robust control of underwater manipulators. To simulate the movement of the robotic manipulators in the underwater environment, the Unified Robot Description Format (URDF) file of a custom-designed electric underwater manipulator is imported into the Simscape Multibody and the hydrodynamic disturbance is modeled according to Morison's equation. Furthermore, the proposed control strategy takes advantage of the universal approximation capability of fuzzy systems to avoid chattering and observe disturbances by adjusting the control gains of classical sliding mode control (CSMC). And adaptive laws are designed to update the parameters of the fuzzy systems. The strong friction caused by the seal is also compensated by actual test data. In the simulation experiments, a special environment of water flow and variable loads is considered. The results demonstrate that the AFSMC strategy can achieve high precision and strong robustness against disturbances for trajectory tracking. More importantly, the chattering caused by CSMC can be eliminated and the hydrodynamic disturbance can be estimated with high precision through the proposed control strategy. [ABSTRACT FROM AUTHOR]

This study provides an adaptive fuzzy control scheme for the class of nonlinear uncertain strict-feedback systems with external disturbances. The backstepping and synergetic control theories are used to develop a robust control approach for this class of systems. The unknown behaviors of the system are estimated through fuzzy systems. The stability is analyzed using the Lyapunov method, which shows that the proposed control method ensures that all the signals of the closed-loop system are bounded, and the tracking error converges approximately to zero. Two simulation examples are given to demonstrate the efficiency of the developed control approach. [ABSTRACT FROM AUTHOR]

Aiming at a more efficient and accurate performance of parallel manipulators in the existence of complex kinematics and dynamics, a robust generalizable methodology is proposed here for an integrated 6-DOF Stewart platform with rotary time-delayed actuators torque control. The suggested method employs a time-delay linear–quadratic integral regulator with online artificial neural network gain adjustment. The unknown time-delay is estimated through a novel robust adaptive estimator. The global asymptotic stability of the estimator is proved via a Lyapunov function. The controller is developed in MATLAB software and implemented on the robot designed in ADAMS software to ensure that the real-time tracking error of a nonlinear system with an unknown time-delay is kept to a minimum. The sensitivity of the controller to the parameter choices is studied via implementing the controller in ADAMS software and is validated by investigating the performance on a naturalistic fabricated robot. The approach is assessed using simulation and experimental tests to show the feasibility, optimum, and zero-error convergence of the technique developed. [ABSTRACT FROM AUTHOR]

This paper deals with modelling and robust control of linear multivariable uncertain systems based on the new linear multivariable ARX (Auto-Regressive with eXogenous input)-Laguerre model and the loop-shaping design procedure with the relative gain array theory. In fact, to guarantee significant parameter number reduction of the multivariable ARX-Laguerre model compared with the classic multivariable ARX model, we propose the optimization of the Laguerre poles of the model using the genetic algorithm where the Fourier coefficients are identified using the recursive least square method. Later, the optimized multivariable ARX-Laguerre model is exploited to propose a robust control algorithm for linear multivariable uncertain systems. Indeed, we propose to combine the loop-shaping design procedure approach and the relative gain array theory to develop a simplified final robust controller guaranteeing reference tracking and robust stability against parametric uncertainties. This proposition aims for the simplification of the control's scheme by adjusting the weighting matrix and the final robust controller calculated from the loop-shaping design procedure for a simpler and more experimentally applicable control scheme. The identification of Fourier coefficients and Laguerre poles as well as the robust multivariable control algorithm are experimentally validated on a laboratory coupled two-tank system showing good results in terms of modelling and attending desired control performances. [ABSTRACT FROM AUTHOR]

In this study, to reduce the impact that permanent magnet linear synchronous motor (PMLSM) servo system on the sensitivity of external and internal interferences, an adaptive super-twisting-based nonsingular fast terminal sliding mode control (AST-NFTSMC) scheme is put forward. First of all, the mathematical model of PMLSM contains uncertainties is set up, and the control law is established to make position signal converge to given state asymptotically. Second, by introducing the super-twisting algorithm, the chattering caused by nonlinear switching function in traditional method is weakened. However, in actual industrial situations, it is difficult to determine the boundary of lumped disturbance, which makes the switching gains in super-twisting algorithm cannot be accurately selected. Therefore, an adaptive law is introduced to adjust the switching gains online, so that the gains can be dynamically adjusted within a limited range during operation, so as to further weaken chattering. Finally, the practicability of AST-NFTSMC is proved in theory and verified by system experiments. The experimental results prove that AST-NFTSMC can significantly weaken chattering, and result in robust control performance. [ABSTRACT FROM AUTHOR]

The four-axis variable trajectory equal-thickness screen (FAVTETS) achieves equal-thickness screening by appropriate excitation force generated by four eccentric rotors in synchronized motion. The forced synchronization exciter is characterized by an unsatisfactory synchronization effect due to the wear of transmission parts. Hence, in this paper, the four-axis controlled synchronization of FAVTETS is investigated, and an intelligent control system is proposed. Firstly, research is conducted on the variable trajectory characteristics of FAVTETS. Next, the sliding mode, fuzzy, and PID controllers are designed and compared to obtain an ideal control effect. Moreover, the influence of torsional stiffness of flexible coupling on control accuracy is considered. The results show that the sliding mode controller has a good control effect. Based on the aforementioned, the simulation model of a four-axis controlled synchronization structure is established via MATLAB/Simulink. Finally, Labview is employed to design the four-axis controlled synchronization software system. Then, the physical experiment is carried out. The four-axis controlled synchronization and vibration trajectory measurement results verify the effectiveness and robustness of the intelligent control system. [ABSTRACT FROM AUTHOR]

The position-force tracking issue of an object being moved by collaborative Multiple Flexible-Joint arms, facing dynamic uncertainties, model nonlinearities, and unknown perturbations is studied in this paper. Toward this end, an adaptive control scheme applying the function approximation technique is suggested, enabling the object to track the reference trajectory. This capability arises from the universal approximation property of the FAT-based approaches. Herein, the q-Bernstein-Schurer operators are exploited to disturbances/uncertain dynamic approximations. Since the parameters of the system are not exactly recognized, adaptive rules are suggested for tuning the coefficients of the operator. The Lyapunov stability analysis guarantees uniformly ultimately bounded stability of all the error signals. Two Flexible-Joint manipulators transporting a rigid object are employed to validate the theoretical achievements. The state-of-the-art Chebyshev Neural Network approximator is also used to compare the suggested methodology. The outcomes exhibit the usefulness of the presented approach, handling the system even in the incidence of uncertainties and disturbances needless to the system's state feedback for function approximation with a low computational burden. [ABSTRACT FROM AUTHOR]

In this paper, the boundary feedback control problem for the Euler–Bernoulli beam with unknown time-varying distributed load and boundary disturbance is investigated. Based on the Lagrangian–Hamiltonian mechanics, the model of the beam is derived as a partial differential equation. To suppress the external disturbance, two disturbance rejection control approaches are adopted in the control design. Firstly, a disturbance observer is designed to estimate the boundary disturbance online. Thus, the effect of the boundary disturbance can be canceled directly in the feedback loop. A time-varying function is applied in the disturbance observer to prevent an excessively large control input. Secondly, a new observer is developed to estimate the upper bound of the disturbance and a sign function is introduced to suppress the influence of the disturbance without demanding the boundedness of the derivative of the boundary disturbance. The well-posedness and the uniform boundedness of the closed-loop system are proved using the operator semigroup theory and the Lyapunov method. Numerical comparisons with existing results are made for demonstrating the advantages of the proposed approaches. [ABSTRACT FROM AUTHOR]

This paper presents a novel robust control algorithm to improve the trajectory tracking accuracy for a class of serial manipulators with unknown uncertainties. Firstly, the manipulators' dynamics is established based on the Lagrangian method, and the intrinsic properties in the dynamical model of uncertain serial manipulators are investigated, resulting in a better match between the dynamical model and the physical systems. Then, based on the upper bound of the uncertainties, a nonlinear robust controller is designed. Here, a higher-order term is invoked in the controller design to further suppress the influence of the uncertainties. As supported by rigorous proofs, the uniform boundness and uniform ultimate boundness of the controlled manipulator under the designed controller are obtained with the Lyapunov–Minimax method. Finally, a numerical simulation and an experiment of the designed controller are implemented on a two-degree-of-freedom manipulator. [ABSTRACT FROM AUTHOR]

This study presents a cross-disciplinary revision of the Little Ice Age (LIA) advance of Nigardsbreen glacier, an outlet from Jostedalsbreen ice cap in western Norway. The associated glacier foreland is characterised by a well-preserved moraine series succeeding the 1748 CE LIA culmination, and a robust age control of individual moraines exists from abundant historical written and pictorial information as well as extensive lichenometric studies. The retreat dynamics of Nigardsbreen ever since the LIA maximum extent was attained is considered well-known. The timing of initiation of the LIA advance and dynamics of the glacier growth prior to reaching its maximum extent, however, is less understood as any moraines predating 1748 CE have been subsequently overridden. Potential archives available for exploring the glacier advance are therefore mostly confined to historical data such as for example, tax records, paintings, and church books, which has resulted in a present-day consensus of the LIA onset of Nigardsbreen c. 1710 CE. However, we show that a lack of adequate critical analysis on the accuracy of published historical data has allowed erroneous ages of glacier terminus positions to manifest in literature, resulting in for example, overestimated glacial advance rates. Here, we combine a novel data set of local tax load directly reflecting glacial impact on farming productivity with a cross-disciplinary assessment of published historical data, including rejection of several data points of former glacier extents. As a result, we present a revised glacier length curve for the LIA advance of Nigardsbreen towards its maximum extent. [ABSTRACT FROM AUTHOR]

In this article, a new multiobjective particle swarm optimization (MOPSO) algorithm is introduced to improve the performance of a sliding mode based robust fuzzy proportional–integral–derivative (PID) controller. In this regard, the non-dominated solution having minimum number of neighbors is considered as the global best position, while the sigma values of the members are employed to determine the personal best position. A modified multiple-crossover operator is combined with the operators of the particle swarm optimization to significantly increase the convergence speed of the algorithm. To limit the size of the archive, a dynamical elimination scheme defined in the Euclidean space is introduced. Besides, iteration-based linear relations are implemented to adaptively compute the inertia weight and learning coefficients. To evaluate the effectiveness of the introduced MOPSO algorithm, the requirements are conducted by means of three benchmark functions with regard to generational distance, spacing, and maximum spread metrics. This analysis demonstrates that the proposed algorithm operates better through comparison with well-known elitist multiobjective evolutionary algorithms. Moreover, the MOPSO algorithm is applied for optimal design of a hybrid robust fuzzy PID controller for a pneumatic system with two bellows. Conflicting objective functions are considered as the normalized values of overshoot and settling time of the displacement between the bellows that should be simultaneously minimized. The feasibility and efficiency of the strategy are assessed in comparison with the conventional controllers. [ABSTRACT FROM AUTHOR]

A new method is developed for the robust stabilization of a Markov jump system with general discrete state time-delay and partly unknown transition probabilities. In contrast to most existing literature, a set of numerical testable conditions, rather than a huge matrix inequality, are established for the resulting closed-loop system in order to justify the stochastic stability and disturbance attenuation capability with the aid of a non-monotonic design approach. To be specific, by constructing a stochastic Lyapunov function via the application of an n -samples variation, sufficient conditions for the existence of a dissipative state feedback controller are derived with less conservativeness, that is, with larger stochastic stable region and better attenuation level. Three examples including a numerical example, a pest's structured population model and an F-404 test aircraft model are presented to demonstrate the advantage and practical potential of the proposed methodology. [ABSTRACT FROM AUTHOR]

In this paper, the autonomous trajectory-tracking problem for an Unmanned Aerial Vehicle (UAV) based on Sliding Mode Control (SMC) algorithms is treated. The control system is implemented in real-time to stabilize a commercial AR.Drone 2.0 quadrotor using monocular vision. The under-actuated mathematical model is based on the Newton-Euler formulation. The algorithm allows the stabilization of the quadrotor in all its states under the simultaneous effect of parametric uncertainties and constant external disturbances. The vision algorithm uses a monocular camera to estimate the vehicle's position. The experimental test results and numerical simulations show the effectiveness and robustness of the proposed controller. [ABSTRACT FROM AUTHOR]

In this article, q -Chlodowsky operators are utilized for synchronizing a chaotic master-slave system. The universal approximation property enables q -Chlodowsky operators to approximate uncertainties, which consist of disturbances and unmodeled dynamics. It is verified that uniformly ultimately bounded stability of the tracking/approximation errors can be assured if the q -Chlodowsky operators are utilized as regressors and the polynomial coefficients are tuned by the adaptive laws calculated in the stability analysis. Moreover, it has been assumed that the rate of synchronization error is not at hand and a filter-based strategy has been adopted instead of designing an observer. The Duffing-Holmes oscillator is studied and the results are also compared with three powerful approximation-based and robust control methods. Unlike neural network/fuzzy estimators in which system states are necessary to define the regressor vector, the proposed uncertainty estimator does not require them in the regressor vector. Furthermore, in comparison with radial basis functions neural networks (RBFNNs), we are involved in fewer adaptive coefficients in the regressor vector of the proposed uncertainty estimator. As a result, the tedious and time-consuming procedure of trial and error for tuning the uncertainty estimator is eliminated. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-time adaptive recursive sliding mode (FTARSM) control scheme is addressed for a steer-by-wire (SbW) automated guided vehicle against model uncertainties and disturbances. First, based on a newly constructed faster fixed-time stable system, a fixed-time recursive sliding structure is developed to guarantee the SbW system fixed-time convergence, where the setting time is independent of initial conditions. By making appropriate initialization settings for the recursive structure, the sliding reaching phase is removed and the control robustness is improved. Then, the extreme learning machine (ELM) is incorporated into the FTARSM controller to estimate the lumped uncertainties upper bound, thus not only the requirement for prior bounds information in controller design is eliminated but also the control chattering is suppressed effectively. Rigorous Lyapunov analyses are further employed to ensure fixed-time closed-loop stability. Finally, the superior performance of the derived control law is verified by experimental results. [ABSTRACT FROM AUTHOR]

This article presents the design, realization, modelling, and control of an aerial manipulator robot capable of performing tasks considered difficult and dangerous for humans. We propose a manipulation system that consists of two subsystems: an aerial platform represented by a hexacopter and a 3 degree-of-freedom manipulator arm that is light and easy to integrate into our hexacopter. The modelling approach of our aerial manipulation system is inspired by the dynamics of floating base systems with tree structures. This type of system presents many control challenges due to system asymmetry, continuous change of inertia, the centre of gravity, manipulator arm effects, and so on. For these reasons, a robust control technique based on a sliding mode controller is proposed to achieve a three-dimensional trajectory-tracking objective. In order to show the effectiveness of the proposed strategy, numerical simulations have been performed in many scenarios. [ABSTRACT FROM AUTHOR]

In this article, the snake robot having nine links with eight joints is considered for serpentine motion in the underwater environment. The movement of a snake robot occurs due to nonlinear drag forces and fluidic torque in underwater conditions. The uncertainties in drag forces and fluidic torque are considered to track the head angle and tangential velocity in this work. The virtual holonomic constraints are formulated to track all the joints by designing a controller for single joint. The parameters of gait pattern are obtained using the sliding surface. The sliding surface is formulated for head link angle and velocity tracking. Super twisting sliding mode control approach is proposed to deal with uncertainties, and results are compared with sliding mode control and adaptive sliding mode control. The robustness of controller is verified by inputting measurement noise. The significant improvement has been observed in chattering indicator and control effort by using the proposed super twisting sliding mode control. The investigation of this research article focuses on how to get almost chattering free operation in underwater uncertain environmental conditions with minimum control effort. [ABSTRACT FROM AUTHOR]

Aiming at the time-delay characteristics and nonlinear planing force of supercavitating vehicles in the process of motion, a parameter-dependent robust controller with anti-saturation compensator is proposed. First, the system model with nonlinear planing force is transformed into a parameter dependent linear-parameter-varying model containing time-delay part and non-time-delay part. Then consider the external disturbance input to design a robust controller and use convex polyhedron theory and the parameter dependence characteristics of controller to ensure the stability of the system with cavitation radius perturbation. Finally, the anti-saturation compensation method is used to overcome the input constraints caused by the physical limitations of the control mechanism. The simulation results show that the controller has good control effect and robust performance for supercavitating vehicles with time-delay characteristics. [ABSTRACT FROM AUTHOR]

This paper presents the attitude control of a rigid satellite in the presence of the total uncertainty of inertia and external disturbance while only outputs of the system are measurable. Noticing the conditions, a new robust back-stepping control for the modified Rodrigues parameters model of the rigid satellite is proposed, at the same time the upper bound of the norm of the total uncertainty vector is estimated adaptively. Due to the inaccessibility of the angular velocity of the system, a finite-time extended observer is used to estimate the angular velocity and total disturbance. The robust stability of the control system is proved by the Lyapunov theory. Finally, a numerical simulation is presented to demonstrate the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper addresses the attitude path design of a remote sensing satellite in various imaging modes. The novel path design algorithm is based on local polynomial regression, which produces a smooth attitude path by receiving the size and timing of maneuvers in each axis according to the desired imaging mode. This algorithm is described for stereo and snapshot modes in an imaging operation. The adaptive robust tracking control (ARTC) law is designed using quaternion algebra to perform the required maneuvers in an attitude path. The ARTC structure includes a sliding mode strategy, a projection-based adaptive model compensation, and a linear feedback term. Suitable conditions for imaging in each mode and the time of taking the image are determined by defining and evaluating the attitude control indices. These indices are defined by the half-cone error along the payload line of sight and relative performance error as a jitter with a 3-sigma confidence level. Despite the challenges in the path design, such as smoothness, system agility, and finite time realization of indices, in a conventional stereo imaging mode, taking an image in the nadir-pointing attitude is neglected. As a result, our work provides suitable conditions for taking the image in this attitude with an interval of 1.2 s. Finally, numerical simulations and verification are performed using multidisciplinary simulation, indicating the effectiveness of the proposed algorithm and model-based ARTC law. [ABSTRACT FROM AUTHOR]

In this work, a new control structure for fully actuated systems that solve the regulation and tracking of trajectories problem is proposed. This controller stands out for its ease of implementation and its ability to attenuate disturbances caused by parametric uncertainties and external forces. The control structure is based on the estimation of the delayed disturbances. Then, the current disturbance is canceled with the delayed disturbance, via the control input. The way in which the dynamics of the system is affected by the residual of these disturbances is analyzed. Also, the necessary conditions for establishing a reduced overshoot, settling time, and an attenuation factor of the disturbance are obtained. The performance of the proposed control structure is illustrated numerically by analyzing the behavior of different second-order single-input–single-output systems and also in the case of a RR-type robot. The control structure was also experimentally implemented in the case of a birotor type drone. [ABSTRACT FROM AUTHOR]

In this paper, a new practical dynamic robust control approach for cooperative robots with inequality constraints is proposed. The controller can compensate errors caused by uncertainties and external disturbances. The inequality constraint is eliminated by choosing proper boundary function and using state transformation. In this way, the controlled output is guaranteed within the desired range. The Lyapunov minimax method is used to prove that the controller can guarantee the uniform boundedness and uniform ultimate boundedness and stability of the robot system. Experimental verifications are carried out on a 2-DOF cooperative robot experimental platform with joint modules. The experimental platform is equipped with a rapid prototyping controller system (CSPACE). Numerical simulation and experimental verification results show that the proposed practical robust controller has significant advantages of trajectory tracking performance and security for cooperative robots with inequality constraints. [ABSTRACT FROM AUTHOR]

In this paper, a novel adaptive robust control approach has been proposed for a class of uncertain mechanical systems. First, aiming for the unknown uncertainties which may be fast time-varying, a novel adaptive mechanism in leakage-type will be developed. Unlike the prevalent adaptive methods, this adaptive mechanism put forward mainly accounts for estimating all the lumped uncertainty terms, and does not require any information of uncertainties other than they are bounded; Second, through transforming the gait following assignment to the constraint control, an adaptive robust constraint-following controller constructed will render the constraints uniformly bounded and uniformly ultimately bounded. To testify the efficacy of proposed approach, a lower limb exoskeleton robot is considered as an illustrative example, the simulations indicate that the proposed control can indeed improve the level of passive rehabilitation training. [ABSTRACT FROM AUTHOR]

In this paper, a robust output feedback controller with error constraint is proposed to improve the position tracking performance of the electro-hydraulic servo system. Since only the position signal of the system is available, a high-order sliding mode observer is designed to estimate the unobtainable system states. The new state observer can not only avoid the influence of sensor measurement noise but also reduce the chattering of traditional sliding mode observer. To cope with the modeling error, parameter uncertainty, and external disturbance, a robust controller based on backstepping method is designed. In addition, barrier Lyapunov function is introduced to limit the maximum tracking error to a preset range. Finally, comparative experiments are carried out on the asymmetric hydraulic cylinder test bench. The experimental result shows that the proposed controller has a satisfied tracking performance. [ABSTRACT FROM AUTHOR]

This paper demonstrates a multiple-input multiple-output (MIMO) controller design framework and a controller switching algorithm for MIMO controllers in their state-space form, which together achieve robust, efficient control of turbocharged lean-burn engines over a wide operating space. The controller design framework requires a linearized plant model, and uses the μ -synthesis and DK-iteration algorithms while considering state and output uncertainties and actuator bandwidths to synthesize a robust H ∞ controller. A controller switching methodology using slow-fast controller decomposition and also incorporating hysteresis at switching points is utilized to smoothly transfer control authority between several MIMO controllers. The approach is applied to a high-fidelity truth-reference GT-Power engine model for a lean-burn natural gas-fueled engine to evaluate the closed-loop controller performance. The multi-tracking control problem targets engine speed, differential pressure across throttle as well as air-to-fuel ratio to achieve satisfactory engine performance and emissions without compressor surge. The engine response obtained using the robust MIMO controller is compared with that obtained using a state-of-the-art benchmark controller to evaluate the additional benefits of the MIMO controller. [ABSTRACT FROM AUTHOR]

This paper investigates the terminal sliding-mode control (TSMC) with predefined-time stability (PTS) for a disturbed quadrotor system (DQS). First, for both the rotational and translational subsystems of the DQS, a novel notion of predefined-time terminal sliding-mode manifold (PTTSMM) is created. Using the proposed PTTSMM method, the DQS state variables reach their origin in a predefined-time. The influence of disturbances is taken into consideration in the design of the suggested control to show its performance. A formal analysis technique is also provided, as well as the stability of the closed-loop DQS. The performance and effectiveness of the predefined-time method proposed in this work are illustrated by numerical simulations and also comparison study with other control techniques is presented. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for generating the best possible climb trajectory that ensures minimum fuel and time efficient climb. The problem is first formulated using standard steady climb equations, which generate a unique combination of flight velocity and flight path angle at each altitude. A possible scenario, such as air density, mass, available power, and required powered variation with altitude, is taken into account when defining the problem. Thereafter, sliding-mode-based trajectory tracking control is formulated with its design procedures, system stability with applied control inputs, finite-time convergence analysis, and complete architecture. A Hansa-3 research aircraft is considered as an example model to demonstrate the work. The findings of generated trajectory are then produced and discussed. In order to follow the design trajectory and achieve the same, the sliding-mode-based control command is supplied. The novelty of the present work lies in proposed strategy of trajectory generation, wherein the aircraft path and velocity are found out to make the fuel and time efficient climb possible. Subsequently, robust control law is developed which shows the applicability of the proposed work on autopilot. The results show that the proposed controller not only controls the aircraft but is also able to follow the design trajectory with minimal errors. To further explore the impact of aircraft mass on climb performance, repeated set simulation is carried out. The outcome is compared with conventional climb, which promises its practical implementation since the proposed solution is simple and compatible to integrate with the existing aircraft autopilot. [ABSTRACT FROM AUTHOR]