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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]

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]

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]

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]

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]

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]

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]

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 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]

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]

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 model-free robust adaptive control scheme with finite-time convergence based on time-delay control is proposed for anti-sway and positioning control of two-dimensional underactuated overhead cranes. First, the whole overhead cranes system is simplified to an ultra-local model for time delay estimation (TDE). TDE brings a direct and effective model-free property but also an estimation error. Second, a sliding mode disturbance observer is designed to estimate and compensate for the TDE error. Third, sliding mode control (SMC) is used to enhance the robustness of the controller. An adaptive integral sliding surface is then designed to accelerate the sliding surface convergence rate and shorten the convergence time. To further optimize the selection of parameters, the parameter estimation is integrated to enhance the performance of model-free control. In the final analysis of the simulation, data yield that the introduction of parameter estimation increases the control performance by more than 20% on average, and the above facts verify the effectiveness of the scheme. Finally, the stability of the closed-loop control system is analyzed by using Lyapunov stability theory, and the effectiveness and robustness of the control scheme are verified through computer simulation results. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of preview sliding mode control for a class of nonlinear uncertain discrete-time singular systems with time-delays. A difference operator approach is used to deal with the controlled system such that the derived augmented systems including preview information of reference signal can be constructed. A suitable surface is proposed in the sense of admissibility by the free-weighed matrix technique. Based on this, a sliding mode controller with preview information is constructed incorporating with the tracking error to ensure that the closed-loop control system reaches the designed sliding mode surface within finite time. To apply the proposed control scheme to the practical engineering systems, the sliding mode tracking controller with preview information is developed for a DC motor based on the proposed control approach. The comparative experiment results demonstrate that the preview information of reference signal can improve the tracking performance. [ABSTRACT FROM AUTHOR]

This paper investigates nonlinear robust fault-tolerant control for turbofan engines with actuator faults. The nonlinear robust fault-tolerant control method is proposed in this paper, which can guarantee the fault tolerance and robustness of turbofan engines when faults and disturbances occur. The design method is implemented in three steps: Firstly, the dynamic effects caused by actuator faults on turbofan engines are analyzed and then the multivariable polynomial state-space model of turbofan engines with actuator faults is proposed. Secondly, appropriate design parameters are chosen according to fault information. Thirdly, the nonlinear robust fault-tolerant control law for turbofan engines with actuator faults is designed by solving an optimization problem. In addition, stability and L 2 gain-like for turbofan engines with bounded disturbances and actuator faults are guaranteed by the proposed nonlinear robust fault-tolerant control method. The distinctive characteristic of the paper is that the nonlinear robust fault-tolerant control method for turbofan engines against actuator faults is proposed which can relax the accuracy requirements of the fault diagnosis subsystem and improve the fault-tolerant performance of the closed-loop control system. Simulations show that the nonlinear robust fault-tolerant control method has better control performances including transient responses, disturbance rejection, and fault tolerance for the turbofan engine with actuator faults. [ABSTRACT FROM AUTHOR]

This paper presents a robust adaptive sliding mode controller scheme as applied to a class of uncertain nonlinear systems with parametric uncertainties and external disturbances. First, a sliding mode control technique is designed. Then, the proposed robust adaptive control schemes are applied to estimate the parametric uncertainties and the upper bound value of the external disturbances by using adaptive laws, ensure robustness in presence of parametric uncertainties and external disturbances, and reduce chattering problem by introducing an hyperbolic tangent function. Lyapunov stability theory is used to analyze the stability of the closed-loop system. As an exemplar, the schemes have been applied to a quadrotor unmanned aerial vehicle (QUAV) model. Simulation results for the control of the QUAV model are provided to illustrate the performance of the proposed robust adaptive sliding mode control scheme and demonstrate that the proposed method has good tracking performance. The simulation results clearly prove the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

This paper proposes a new robust output-feedback adaptive event-triggered control (AETC) method for linear systems with parametric uncertainties. The proposed event-triggered mechanism (ETM) is obtained based on the L 2 stability condition. In this paper, two design approaches are presented, the emulation approach (pre-designed control gain) and the co-design approach. In the latter, the event-triggering law and the output-feedback controller are designed simultaneously to have a more efficient control system. The proposed adaptive event-triggered mechanism (AETM) in both approaches leads to an increase in the average of inter-event times based on linear matrix inequalities (LMIs). Consequently, in the proposed methods, the stability of the event-based system is ensured, the Zeno phenomenon is avoided, the feasibility margin and the quality of the response are well maintained, and the number of samplings is reduced, considerably. Finally, to indicate the capability of the proposed methods, two numerical simulations are presented. [ABSTRACT FROM AUTHOR]

The main objective of this article is to solve the trajectory following problem for lower limb exoskeleton robot by using a novel adaptive robust control method. The uncertainties are considered in lower limb exoskeleton robot system which include initial condition offset, joint resistance, structural vibration, and environmental interferences. They are time-varying and have unknown boundaries. We express the trajectory following problem as a servo constraint problem. In contrast to conventional control methods, Udwadia–Kalaba theory does not make any linearization or approximations. Udwadia–Kalaba theory is adopted to derive the closed-form constrained equation of motion and design the proposed control. We also put forward an adaptive law as a performance index whose type is leakage. The proposed control approach ensures the uniform boundedness and uniform ultimate boundedness of the lower limb exoskeleton robot which are demonstrated via the Lyapunov method. Finally, simulation results have shown the tracking effect of the approach presented in this article. [ABSTRACT FROM AUTHOR]

Motion control of mechatronic systems with uncertainties and physical constraints, while ensuring robustness and achieving better performance, such as high tracking accuracy and fast response, has always been a hot topic. However, the most current related works only focus on how to guarantee system stability under constraints, and few consider comprehensive performance. This paper investigates gated recurrent unit (GRU)-based compensation adaptive robust control (ARC) for uncertain linear motor–driven stage system with state and input constraints. To achieve rapid and precise motion control, a dual-loop control structure is employed, where GRU and ARC are the outer loop and the inner loop, respectively. First, the ARC control law is used to deal with the parameters uncertainty and external disturbances in the system, which further improves the tracking accuracy. A GRU neural network is then constructed and capable of implementing precise prediction ahead of the actual system output. Through choosing suitable loss function and training model, it can effectively minimize prediction error under state and input constraints. Comparative experiment results demonstrate the superiority and validity of the proposed scheme on the basis of GRU and ARC. [ABSTRACT FROM AUTHOR]

The coupling, nonlinearity, and uncertainty characteristics of vehicle dynamics make the accurate longitudinal and lateral control of an automated and connected vehicle platoon a tough task. Little research has been conducted to fully address the characteristics. By using the ideology of constraint-following control this article proposes an integrated longitudinal and lateral adaptive robust control methodology for a vehicle platoon with a bidirectional communication topology. The platoon control objectives contain the path tracking stability, the platoon internal stability, and the string stability. First, we establish the nonlinear kinematics path tracking model and the coupled vehicle longitudinal and lateral dynamical model that contains time-varying uncertainties. Second, we design a series of nonlinear equality constraints that directly guarantee the control objectives based on the kinematic relations. On this basis, an adaptive robust constraint-following control is proposed. It is shown that the control guarantees the uniform boundedness and the uniform ultimate boundedness of the constraint-following error and the uncertainty estimation error. Finally, simulation results are provided to validate the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

This article proposes a computationally efficient adaptive robust control scheme for a quad-rotor with cable-suspended payloads. Motion of payload introduces unknown disturbances that affect the performance of the quad-rotor controlled with conventional schemes, thus novel adaptive robust controllers with both integer- and fractional-order dynamics are proposed for the trajectory tracking of quad-rotor with cable-suspended payload. The disturbances acting on quad-rotor due to the payload motion are estimated by utilizing adaptive laws derived from integer- and fractional-order Lyapunov functions. The stability of the proposed control systems is guaranteed using integer- and fractional-order Lyapunov theorems. Overall, three variants of the control schemes, namely adaptive fractional-order sliding mode (AFSMC), adaptive sliding mode (ASMC), and classical Sliding mode controllers (SMC)s) are tested using processor in the loop experiments, and based on the two performance indicators, namely robustness and computational resource utilization, the best control scheme is evaluated. From the results presented, it is verified that ASMC scheme exhibits comparable robustness as of SMC and AFSMC, while it utilizes less sources as compared to AFSMC. [ABSTRACT FROM AUTHOR]

In this study, a robust adaptive controller is designed to be used in an active tuned mass damper system that can be used to damp undesired vibrations that occurred on the multistory buildings during the earthquake. To realize the controller design, all of the system parameters are assumed to be unknown, and the adaptive structure of the designed controller is obtained by designing adaptive compensation rules for system parameters. A backstepping control design approach is utilized for the control design by considering the appropriateness of the system's structure of multistory buildings having an active tuned mass damper system at the top of the structure. The proposed control design is supported with a Lyapunov-based stability analysis where it is proven that the designed controller is able to protect the overall system's stability while reaching the main control purpose. In addition to these, in the simulation studies realized for a nine-story building under the effect of a major earthquake, it is shown that the designed controller can be used to reach the main control purpose efficiently. [ABSTRACT FROM AUTHOR]

In the past few years, many studies have proved the efficiency of Simple Adaptive Control (SAC) in mitigating earthquakes' damages to building structures. Nevertheless, the weighting matrices of this controller should be selected after a large number of sensitivity analyses. This step is time-consuming and it will not necessarily yield a controller with optimum performance. In the current study, an innovative method is introduced to tuning the SAC's weighting matrices, which dispenses with excessive sensitivity analysis. In this regard, we try to define an optimization problem using intelligent evolutionary algorithm and utilized control indices in an objective function. The efficiency of the introduced method is investigated in 6-story building structure equipped with magnetorheological dampers under different seismic actions with and without uncertainty in the model of the proposed structure. The results indicate that the controller designed by the introduced method has a desirable performance under different conditions of uncertainty in the model. Furthermore, it improves the seismic performance of structure as compared to controllers designed through sensitivity analysis. [ABSTRACT FROM AUTHOR]

This paper studies a high-accuracy motion control method named output feedback adaptive robust control for a dc motor with uncertain nonlinearities and parametric uncertainties, which always exist in physical servo systems and deteriorate their tracking performance. As only position signal is measurable, a uniform robust exact differentiator (URED) for the unmeasurable states and adaptive control for the parametric uncertainties are integrated in the model compensation term; and the robust control is applied to handle uncertain nonlinearities and stabilize the system. Then, the stability of the closed-loop system is proved theoretically. Finally, simulation and experimental results are studied for a dc motor system to prove the control performance of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper presents an integrated nonlinear robust adaptive controller with uncertainty observer for active front wheel steering system and direct yaw moment control system. First, an integrated vehicle chassis control model is established as the nominal model with the additive and multiplicative uncertainties of the system. Secondly, an integrated nonlinear robust adaptive control law with the additive uncertainty observer is designed via Lyapunov stability theory to calculate the corrective yaw moment, and an adaptive law is designed based on projection correction method to online estimate and compensate the multiplicative uncertainty of the system. Then, the constrained optimal allocation problem of the corrective yaw moment is transformed into the nonlinear optimization problem, and the sequential quadratic programming method is used to solve the nonlinear optimization problem to coordinate active front wheel steering system and direct yaw moment control system. Finally, the performance of the proposed integrated nonlinear robust adaptive controller is verified via vehicle dynamics simulation software. [ABSTRACT FROM AUTHOR]

This article investigates the design of a novel nonlinear robust adaptive control architecture to stabilize and control an airplane in the presence of left-wing damage. Damage effect is modeled by considering the sudden mass and inertia changes, center of gravity, and aerodynamic variations. The novel nonlinear control algorithm applies a state predictor as well as the error between the real damaged dynamics and a virtual model based on the nominal aircraft dynamics in the control loop of the adaptive strategy. The projection operator is used for the purpose of robustness of the adaptive control algorithm. The stability of the proposed nonlinear robust adaptive controller is demonstrated applying the Lyapunov stability theory. The performance of the proposed controller is compared with two previous successful algorithms, which are implemented on the Generic Transport Model airplane to accommodate wing damage. Numerical simulations demonstrate the effectiveness and advantages of the proposed robust adaptive algorithm regarding two other algorithms of adaptive sliding mode and L 1 adaptive control. [ABSTRACT FROM AUTHOR]

In this study, a nonlinear adaptive controller that can be used to control a magnetic levitation (maglev) is designed. The designed controller is equipped with a nonlinear velocity observer to provide the control without measuring velocity. Its capability to adaptively compensate all parametric uncertainties during the control process is one of the main advantages of this controller. Utilizing this capability, control of the maglev system can be realized without using any knowledge about system parameters. Due to the fast convergence capability of the designed observer and the desired model dependent structure of the adaptation rules, the proposed control design provides better performance than most of the robust and adaptive controllers that have been frequently used to control maglev system. The observer dynamics are analyzed via a Lyapunov–like preliminary analysis. Then, convergence of the observation and the tracking errors under the closed–loop operation and stability of the closed–loop error dynamics are proven via a Lyapunov–based stability analysis where the result obtained in the mentioned preliminary analysis is used. Performance of the designed observer–controller couple is demonstrated via experimental results. The efficiency of the designed controller is tested against a robust proportional–integral–derivative (PID) controller and an another Lyapunov–based nonlinear robust controller called as robust integral of sign of error (RISE) controller. Experimental results show that the designed controller performs the best tracking performance with the least control effort among these three controllers. [ABSTRACT FROM AUTHOR]

This article deals with the robust optimal control and identification of uncertain adaptive cruise control systems. Both measurement delay and engine's lag are investigated in system modeling and control design. The control structure consists of two steps. In the first step, by using a new approach, the uncertain parameters of longitudinal dynamics of each vehicle is identified. Afterwards, at the second step, by using the relative position and velocity measurement with respect to ahead vehicle, a robust control against size changing of platoon is presented to assure the internal stability, string stability, and safety of heterogeneous vehicular platoons. A cost function involving important metrics internal stability, maximum overshoot, and settling time is introduced, and the particle swarm optimization algorithm is used to find the optimal values of control parameters minimizing the cost function. It will be shown that the proposed robust controller guarantees the internal stability, string stability, and safety of adaptive cruise control systems in the presence of measurement and parasitic delays. Several simulation results are provided to show the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]

An adaptive hybrid controller is proposed for reducing the unbalanced vibration response of a flexible rotor/active magnetic bearing system. It is observed that conventional adaptive feedforward controller (AFFC) normally used in the active noise control is very sensitive in performance for changes in rotor spin frequencies. Although frequency updating is a part of its architecture, a small practical variation in the rotor spin frequency can reduce its effectiveness drastically. A smart combination of adaptive notch filter and Goertzel filter is proposed for the frequency estimation. During changes of the rotor spin frequency, fundamental harmonics of the flexible rotor are excited. By using hybrid controllers that combine feedback control and AFFC, the amplitude of these fundamental harmonics is reduced significantly. By applying the multi-harmonic hybrid control, the multiple harmonics generated due to coupling misalignment are compensated efficiently. Fourier transform of the control signal is further used to detect the presence of the coupling misalignment. [ABSTRACT FROM AUTHOR]

Autonomous underwater vehicles (AUVs) are highly nonlinear underactuated systems with uncertain dynamics and a challenging control problem. The main focus of this paper is to present a control law that shows desirable performance in the presence of modeling uncertainties. In this study, uncertainties are considered to be bounded and the AUV mathematical model is obtained in the presence of such uncertainties. Forces and torques applied to the AUV are also designed using a nonlinear dynamic controller. Appropriate adaptive rules are also presented to overcome system uncertainties and external disturbances. The adaptive nonlinear dynamic controller is designed based on upper bounds of system uncertainties and its stability is proven using the Lyapunov theory. In this article, the performance of the proposed control algorithm for tracking reference trajectories in an obstacle-rich environment is investigated. Therefore, the control algorithm is combined with potential fields for obstacle avoidance. Obtained results show the efficiency of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive robust control algorithm for the nonlinear dynamics of robot manipulators with unknown backlash in gears. The basic nonlinear model of a serial manipulator robot is used for the controller design, and this is combined with the nonlinear proposed dead zone model, based on the input and output torque. The main idea of providing this model is to achieve a dynamic model of the system considering the backlash of the robot joint gears, and having less complexity such that the developed controller does not need the inverse backlash model. The adaptive robust controller is developed, without using the inverse backlash model. The proposed controller is designed based on an unknown dead zone parameter and it guarantees the stability and path tracking of the robot trajectory with unknown dead zone parameter in the desired range. Numerical simulations are conducted to show the effectiveness of the proposed controller. Finally, the efficiency and capability of the proposed controller in dealing with the unknown backlash nonlinearities in gears of the manipulator are demonstrated by experimental results with a five-bar manipulator. [ABSTRACT FROM AUTHOR]

Designing a controller for multi-body systems including flexible and rigid bodies has always been one of the major engineering challenges. Equations of motion of these systems comprise extremely nonlinear and coupled terms. Vibrations of flexible bodies affect sensors of rigid bodies and might make the system unstable. Introducing a new control strategy for designing control systems which do not require the rigid–flexible coupling model and can dwindle vibrations without sensors or actuators on flexible bodies is the purpose of this paper. In this study, a spacecraft comprising a rigid body and a flexible panel is used as the case study, and its equations of motion are extracted using Lagrange equations in terms of quasi-coordinates. For oscillations on a rigid body to be eliminated, a frequency estimation algorithm and an adaptive filtering are used. A controller is designed based on the rigid model of the system, and then robust stability conditions for the rigid–flexible system are obtained. The conditions are also developed for the spacecraft with more than one active frequency. Finally, the robust adaptive vibration control system is simulated in the presence of resonance. Simulations' results indicate the advantage of the control method even when several active frequencies simultaneously resonate the dynamics system. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of robust adaptive finite-time tracking control for a class of mechanical systems in the presence of model uncertainties, unknown external disturbances, and input nonlinearities containing saturation and deadzone. Without imposing any conditions on the model uncertainties, radial basis function neural networks are used to approximate unknown nonlinear continuous functions, and an adaptive tracking control scheme is proposed by exploiting the recursive design method. It is shown that the input saturation and deadzone model can be expressed as a simple linear system with a time-varying gain and bounded disturbance. An adaptive compensation term for the upper bound of the lumped disturbance is introduced. The semi-global finite-time uniform ultimate boundedness of the corresponding closed-loop tracking error system is proved with the help of the finite-time Lyapunov stability theory. Finally, an example is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the finite time spacecraft attitude tracking control problem, while considering modeling uncertainty, external disturbances and control input saturation. A novel integral terminal sliding mode surface (ITSMS) is designed by combining the fast terminal sliding mode surface (FTSMS) with a low pass filter to achieve a fast finite time convergence rate for the control system, without input singularity. An auxiliary signal is used to compensate for the effects of actuator saturation. The basic controller is first formulated based on the ITSMS, fast-TSM-type reaching law and auxiliary system, in the presence of an external disturbance and input saturation. Then, an adaptive control procedure is introduced, which simultaneously handles modeling uncertainty and external disturbance, thereby creating an adaptive attitude tracking controller. The proposed controller provides a fast finite time convergence rate for the control system, based on the newly designed ITSMS, while simultaneously compensating for modeling uncertainty, external disturbances and input saturation, without restricting the parameter selection process nor requiring repeated differentiation of nonlinear functions. Finally, digital simulation results are presented and demonstrate the effectiveness of the proposed controllers. [ABSTRACT FROM AUTHOR]

This work presents a novel adaptive fuzzy controller based on the inversely fuzzified values associated with the H infinity technique and it is applied to vibration control of a vehicle seat suspension system installed with a magneto-rheological damper. In this work, the fuzzified values are embedded into the Riccati-like equation to achieve enhanced robustness of control function and the sliding surface function of sliding mode control is used for designing the main control function. The synthetic function of controller includes a model of online interval type 2 fuzzy neural network system and a fast calculation for clustering. The combination between the fuzzy model system and the proposed control algorithm can shorten the calculation time and improve control responses of the system in the presence of disturbances and uncertainties. After formulating the controller, the effectiveness is validated through both simulation and experiment. In computer simulation, three different road profiles of random bump, regular bump, and random step wave are adopted to emulate severe external disturbances. It is shown from the simulation that both displacement and acceleration of the driver are remarkably well controlled under three different road conditions. This advantage is also validated in the experimental work. It is demonstrated that vibration control performances under random step wave road are much better than the comparative adaptive fuzzy controller. It is identified from the results that the use of the inversely fuzzified values plays a major role to enhance the robustness and hence better control responses in the presence of the disturbances. [ABSTRACT FROM AUTHOR]

In this paper, a new backstepping type 2 fuzzy control is developed for a class of uncertain multi-inputs multi-outputs (MIMO) chaotic systems, with a complicate of uncertainties and external disturbances. The system consists of interconnected subsystems that are duffing equation. In the control design, type 2 fuzzy logic systems are used to approximate the unknown functions. Hybrid adaptive robust tracking control schemes that are based upon a combination of bounds of type 2 fuzzy approximation parameters and the backstepping design are developed such that all the states and signals are bounded and the proposed approach alleviate the online computation burden and improves the robustness to dynamic uncertainties and external disturbances. Finally, the control of chaotic duffing systems with unknown parameters is given as example to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Temperature control in a cryogenic wind tunnel is the key to realizing finely controlled Reynolds number close to true flight. This study deploys the L1 adaptive control methodology to ensure the total temperature profile of the cryogenic wind tunnel tracks a specified reference trajectory. After introducing a non-linear model of a cryogenic wind tunnel and a linear temperature model, a linear–quadratic–Gaussian (LQG) controller is implemented as the baseline controller. The L1 adaptive controller with piecewise constant adaptive law is used as an augmentation to the baseline controller to cancel the matched and unmatched uncertainties within the actuator’s bandwidth. By introducing two modifications to the standard L1 adaptive controller, which are the transportation delay modelling in the state predictor and the non-linear state dependent filter, the L1 adaptive controller improves the performance of the baseline controller in the presence of uncertainties in temperature control, guaranteeing proper stability and delay margin. The simulation results and analysis demonstrate the effectiveness of the proposed control architecture. The main contribution of this paper lies in the first applications of L1 adaptive control to the wind tunnel control problem and the non-linear state dependent filter in L1 adaptive control structure. [ABSTRACT FROM AUTHOR]

An immense body of research has focused on nonlinear vibration energy harvesting systems mainly because of the inherent narrow bandwidth of their linear counterparts. However, nonlinear systems driven by harmonic excitation often exhibit coexisting periodic or chaotic attractors. For effective energy harvesting, it is always desired to operate on the high-energy periodic orbits; therefore, it is crucial for the harvester to move to the desired attractor once the system is trapped in any other coexisting attractor. Here we propose a robust and adaptive sliding mode controller to move the nonlinear harvester to any desired attractor by a short entrainment on the desired attractor. The proposed controller is robust to disturbances and unmodeled dynamics and adaptive to the system parameters. The results show that the controller can successfully move the harvester to the desired attractor, even when the parameters are unknown, in a reasonable period of time, in less than 30 cycles of the excitation force. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive robust controller with uniform robust exact differentiator has been proposed for a class of nonlinear systems with structured and unstructured uncertainties. The adaptive robust controller is integrated with an uniform robust differentiator to handle the problem of the incalculable part of the derivative of virtual controls and the differential explosion happened in backstepping techniques. The stability of the closed loop system is demonstrated via Lyapunov method ensuring a prescribed transient and tracking performance. Simulation and experimental results are carried out to verify the advantages of the proposed method. [ABSTRACT FROM AUTHOR]

This paper offers an adaptive global second-order sliding surface for perturbed dynamical systems with matched and unmatched external disturbances. Based on the composite nonlinear feedback theory, a nonlinear function Ψ(x1) is employed in the switching surface to adjust the damping ratio of the controlled system. Initially, using a constant gain matrix, a small value of the damping ratio is achieved presenting a fast performance. As the system state converges to the origin, the damping ratio of the closed-loop system is increased that yields fast settling time and a low overshoot. A novel smooth and chattering-free controller is proposed to fulfill the removal of the reaching mode and the existence of the sliding behavior around the surface from the beginning. The adaptive gain tuning controller reduces the required information for the upper bound of disturbances. Moreover, the selection of the constant parameters μ1 and τ1 for the control law is turned into a cost function and solved by a particle swarm optimization method. Several criteria are derived to assure the robust stability of the uncertain dynamical system. Some simulations are offered to demonstrate the effectiveness of the planned technique. [ABSTRACT FROM AUTHOR]

In this paper, a perturbation observer-based adaptive passive control scheme is developed to provide great robustness of nonlinear systems against the unpredictable uncertainties and disturbances therein. The proposed scheme includes a high-gain perturbation observer and a robust passive controller. The high-gain perturbation observer is designed to estimate online the perturbation aggregated from the combinatorial effect of system nonlinearity, parameter uncertainty, unmodelled dynamics and fast time-varying external disturbances. Then the robust passive controller, using the estimated perturbation, can produce the minimal control effort needed to compensate for the magnitude of the actual current perturbation. Furthermore, the convergence of estimation error of the high-gain perturbation observer and the closed-loop system stability are analyzed theoretically. Finally, two practical examples are given to show the effectiveness and advantages of the proposed approach over the accurate model-based passive control scheme and the linearly parametric estimation-based adaptive passive control scheme. [ABSTRACT FROM AUTHOR]

This paper proposes a new robust adaptive law for adaptive control of vehicle active suspensions with unknown dynamics (e.g. non-linear springs and piece-wise dampers), where precise estimation of essential vehicle parameters (e.g. mass of vehicle body, mass moment of inertia for the pitch motions) may be achieved. This adaptive law is designed by introducing a novel leakage term with the parameter estimation error, such that exponential convergence of both the tracking error and parameter estimation error may be proved simultaneously. Appropriate comparisons with several traditional adaptive laws (e.g. gradient and σ-modification method) concerning the convergence and robustness are presented. The mitigation of the vertical and pitch displacements can be achieved with the proposed control to improve the ride comfort. The suspension space limitation and the tyre road holding are also studied. A dynamic simulator consisting of commercial vehicle simulation software Carsim® and Matlab® is built to validate the efficacy of the proposed control scheme and to illustrate the improved estimation performance with the new adaptive law. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of the high-performance motion loading control of an electro-hydraulic load simulator (EHLS). To begin with, the non-linear motion loading model of the EHLS was developed, by which the external disturbances caused by actuator active motion and the uncertainties arising from the EHLS were comprehensively considered. To address these uncertainties and disturbances, the adaptive robust torque control algorithm was developed with the motion loading model. In contrast to the available control methods concerning the EHLS, the developed method has two advantages. First, instead of performing the fixed coefficients-based linear feed-forward compensation using the actuator velocity, adaptive non-linear feed-forward compensation is achieved through the back-stepping design procedure. Second, the uncertainties and disturbances including system parametric uncertainties, un-modelled friction dynamics and unknown external disturbance are addressed comprehensively. Besides illustrating the theoretical proof, the effectiveness of the proposed method is verified through comparative experiments. [ABSTRACT FROM AUTHOR]

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

This paper investigates a finite-time attitude manoeuvre control problem for a flexible spacecraft subject to bounded external disturbances. A robust discontinuous finite-time controller with terminal sliding mode control is designed to solve this problem provided that the disturbances and the coupling effect of flexible modes are bounded with a known boundary. The controller is further enhanced by an adaptive scheme to deal with the more practical case that the boundary is unknown. The enhanced version is continuous and chattering-free. The results are rigorously proved using the Lyapunov stability theory. The effectiveness and robustness of the proposed controllers are demonstrated by numerical simulation. [ABSTRACT FROM AUTHOR]

This paper discusses the global robust output regulation problem for a class of nonlinear output feedback systems. It is assumed that the exosystem and the high-frequency gain sign are unknown and that the unknown parameters can be arbitrarily large. To solve this problem, two major challenges are to be overcome. First, the concurrence of the unknown exosystem and the unknown high-frequency gain sign cannot be handled merely by designing estimators for the two unknown parameters respectively. Second, the conventional extended matching design approach cannot be directly implemented, owing to the arbitrarily large unknown parameters. To cope with these difficulties, a new estimator is developed, and the extended matching design approach is modified to obtain a suitable update law for the estimator. The effectiveness of the proposed adaptive controller is illustrated by an example. [ABSTRACT FROM AUTHOR]

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

This paper presents adaptive time-delay control (TDC) with a supervising switching technique (SST) for controlling robot manipulators. Two adaptive techniques are used to enhance the TDC. The control gain of TDC is adaptively tuned using a class of Nussbaum functions. With Nussbaum functions, compared with conventional TDC using a constant gain, the proposed control using Nussbaum functions can deal with inertia parameter variations due to the movement of a robot manipulator. The SST is used to deal with discontinuous disturbances. The proposed control is model-free, highly accurate, robust and adaptive. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive robust output feedback control approach is proposed for a class of uncertain non-linear systems with unknown input deadzone non-linearity, unknown failures and unknown bounded disturbances. By constructing the dead-zone inverse and applying the backstepping recursive design technique, a robust adaptive backstepping controller is proposed, in which adaptive control law is synthesized to handle parametric uncertainties and a novel robust control law to attenuate disturbances. The robust output feedback control law is developed by integrating a switching function s algorithm at each step of the backstepping design procedure. In addition, K-filters are designed to estimate the unmeasured states and neural networks are employed to approximate the unknown non-linear functions. By ensuring boundedness of the barrier Lyapunov function, the major feature of the proposed controller is that it can theoretically guarantee asymptotic output tracking performance, in spite of the presence of unknown input dead-zone non-linearity, various actuator failures and unknown bounded disturbances via Lyapunov stability analysis. The effectiveness of the proposed approach is illustrated by the simulation examples. [ABSTRACT FROM AUTHOR]