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In this paper, we propose a nonlinear state feedback controller based on linear matrix inequality (LMI) for a class of nonlinear systems with parametric uncertainties and external disturbances. The primary goals of the proposed controller are to guarantee system stability and performance in the presence of system uncertainties and time-dependent disturbances. To meet the specified objectives, the LMI form is calculated as a hierarchical control structure. Using the Lyapunov stability function, the asymptotic stability of the nominal system obtained from the nonlinear state feedback is proven, and the LMI condition is attained. After applying the nonlinear state feedback controller, asymptotic stability conditions for the nominal system are constructed using the Lyapunov function, and the nonlinear state-feedback control mechanism is determined accordingly. Considering the external disturbance as input, the terms of the state matrices are substituted in the obtained LMI, and the LMI condition for a nominal system is achieved in the presence of disturbances. The asymptotic stability condition of the uncertain system in the presence of external disturbances is determined by adding uncertainties to the system. The proposed approach yields a simple control mechanism representing an independent of system order. The performance of the proposed approach was assessed using a simulation study of a ball and beam system. [ABSTRACT FROM AUTHOR]

Abstract In this paper, we address the vibration abatement problem of a flexible riser system preceded by nonlinear input saturation characteristic and uncertainties of the system. By virtue of Lyapunov theory, auxiliary system and robust control strategy, a boundary robust adaptive anti-saturation control is developed to restrain the vibration, remove the nonlinear input saturation effects and compensate for the uncertainties of system parameters and boundary disturbance. Applying the rigorous analysis without simplifying or discretizing the partial differential equation dynamics, the controlled system is ensured to be uniformly bounded stable with the designed control law. In the end, simulation results are presented for control performance verification. Highlights • A boundary robust adaptive anti-saturation control is presented to suppress the riser's vibration. • The online updating laws are developed to compensate the uncertainties of system. • The auxiliary system is introduced to handle the input saturation. • The σ-modification is exploited to adjust the robustness of the system. • The stability of the closed-loop system is proved via rigorous Lyapunov analysis. [ABSTRACT FROM AUTHOR]

A realistic control paradigm should concurrently account for different sources of uncertainty such as those in modeling parameters, external disturbances and noise, as well as operational cost. Yet, this is a daunting task for which many current control approaches lack in one aspect or the other. In particular, the consumed control energy is an important aspect of controller design that is often ignored. In this paper, we propose a stable robust adaptive interval type-2 fuzzy H 2 /H ∞ controller (RAIT2FH 2 H ∞ C) for a class of uncertain nonlinear systems that aims to address the above concerns through its hybrid robust/adaptive structure. In particular, the H 2 energy and tracking cost function is minimized with respect to a H ∞ disturbance attenuation constraint, while the adaptive interval fuzzy logic system (IT2FLS) handles the uncertainties in approximating the unknown nonlinear dynamics of the system. In principle, the interval fuzzy logic approach aims to manage portions of uncertainty that could not be precisiated, leading to improved error performance. Several simulation studies, with or without disturbance and noisy measurements, as well as actual experimental implementation on a 3-PSP (prismatic-spherical-prismatic) parallel robot confirm this assessment. More specifically, in comparison with a competing methodology as well as its type-1 counterpart, the proposed interval type-2 strategy expends better or comparative control effort while reaching considerably better tracking performance. [ABSTRACT FROM AUTHOR]

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

The sliding mode control (SMC) technique with a first-order low-pass filter (LPF) is incorporated with a new adaptive PID controller. It is proposed for tracking control of an uncertain nonlinear system. In the proposed control scheme, the adaptation law is able to update the PID controller online during the control process within a short period. The chattering phenomenon of the SMC can be alleviated by incorporation of a first-order LPF, while the robustness of the control system is similar to that of the sliding mode. In the closed-loop control analysis, the convergence condition in the reaching phase and the existence condition of the sliding mode were analyzed. The stability of the closed-loop control is guaranteed in the sense of Lyapunov’s direct method. The simulations and experimental applications of a speed tracking control of a spark ignition (SI) engine via electronic throttle valve control architecture are provided to verify the effectiveness and the feasibility of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we study the cooperative global adaptive output regulation problem for a class of nonlinear uncertain multi-agent systems subject to an uncertain leader system. In comparison with the case where the leader system is known exactly, we need to combine adaptive control and robust control techniques to deal with the unknown parameters in the leader system. By employing a distributed internal model for the multi-agent system, we first convert the problem into a global adaptive robust stabilization problem of a distributed augmented system. Then we further solve the global adaptive stabilization problem of the augmented system by a distributed adaptive control law. Finally, we show that the unknown parameters in the leader system can be exactly estimated provided that the distributed internal model is of minimal order. [Copyright &y& Elsevier]

In this paper, a robust adaptive neural control design approach is presented for a class of uncertain pure-feedback nonlinear systems. To reduce the complexity of the both controller structure and computation, only one neural network is used to approximate the lumped unknown function of the system at the last step of the recursive design process. By this approach, the complexity growing problem existing in conventional methods can be eliminated completely. Stability analysis shows that all the closed-loop system signals are uniformly ultimately bounded, and the steady state tracking error can be made arbitrarily small by appropriately choosing control parameters. Simulation results demonstrate the effectiveness and merits of the proposed approach. [ABSTRACT FROM AUTHOR]

This letter addresses the performance study of an adaptive controller in the presence of gain and delay uncertainties. The nonlinearities in the controller presented here do not allow an analytical study of the effect of uncertainties on performance. A numerical study is done instead using the sampling, learning, prediction, and optimization capabilities of the software Global Optimization, Sensitivity and Uncertainty in Models (GoSUM). [ABSTRACT FROM PUBLISHER]

In this brief, a fault detection and isolation (FDI) method is developed for aircraft engines by utilizing nonlinear adaptive estimation techniques. The fault diagnosis method follows a general architecture developed in previous papers, where a fault detection estimator is used for fault detection, and a bank of nonlinear adaptive fault isolation estimators are employed to determine the particular fault type/location. Each isolation estimator is designed based on the functional structure of a particular fault type under consideration. The general FDI architecture is applied to a realistic nonlinear aircraft engine model recently developed by NASA Researchers. In addition, the robustness of the fault diagnostic method with respect to normal engine health degradation is enhanced by adaptive thresholds and adaptive approximation techniques, hence accurate diagnostic performance is maintained while the engine continues to degrade over its lifetime. Some representative simulation results are given to show the effectiveness of the robust nonlinear FDI method. [ABSTRACT FROM PUBLISHER]

A robust adaptive neural network controller is proposed for a class of uncertain non-linear time-delay systems in strict feedback form with both completely unknown control gains and unknown non-symmetric dead-zone non-linearity based on backstepping design. The proposed design approach does not require a priori knowledge of the signs of the unknown control gains. The unknown time delays are compensated for constructing appropriate Lyapunov-Krasovskii functionals. By utilising integral Lyapunov design and sliding-mode control strategy, the controller singularity problem and the effect of dead-zone input non-linearity are avoided perfectly. From Lyapunov stability theorem, it is proved that the proposed design approach is able to guarantee semi-globally uniformly ultimately boundedness of all the signals in the closed-loop system, and the tracking error of the system is proven to be converged to a small neighbourhood of the origin. The simulation results demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper proposes a robust self-organizing neural-fuzzy-control (RSONFC) scheme for a class of uncertain nonlinear multiple-input–multiple-output (MIMO) systems. We first develop a self-organizing neural-fuzzy network (SONFN) with concurrent structure and parameter learning. The fuzzy rules of SONFN are generated or pruned systematically. The proposed RSONFC scheme comprises an SONFN identifier, an uncertainty observer, and a supervisory controller. The SONFN identifier functions as the principal controller, and the uncertainty observer is designed to oversee uncertainties within the compound system. The supervisory controller combines sliding-mode control (SMC) and an adaptive bound-estimation scheme with various weights to achieve H_\infty tracking performance with a desired level of attenuation. Projection-type adaptation laws of network parameters developed using the Lyapunov's synthesis approach guarantee the stability of the overall control system. Simulation studies on a single-link flexible-joint manipulator and a two-link robot demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, the problems of stability and control for a class of uncertain nonlinear systems with unknown state time-delay are studied by using the fuzzy logic systems. Because the dynamic surface control technique is introduced to deal with the uncertain time-delay systems, the designed adaptive fuzzy controller can avoid the issue of "explosion of complexity", which comes from the traditional backstepping design procedure. Compared with the existing results in the literature, the robustness to the fuzzy approximation errors is improved by adjusting the estimations of the unknown bounds for the approximation errors. It is shown that the resulting closed-loop system is stable in the sense that all the signals are bounded and the system output track the reference signal in a small neighborhood of the origin by choosing design parameters appropriately. Three simulation examples are given to demonstrate the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, a robust intelligent tracking control (RITC) system employs an adaptive output recurrent cerebellar model articulation controller (ORCMAC) is developed for uncertain nonlinear system to achieve H ∞ tracking performance. The proposed dynamic structure of ORCMAC has superior capability in efficient learning mechanism and dynamic response. Temporal relations are embedded in conventional cerebellar model articulation controller (CMAC) by adding feedback connections between the output space and input space, so that the ORCMAC captures the system dynamic. In the RITC design, the Taylor linearization technique is employed to increase the learning ability of ORCMAC and the on-line adaptive laws are derived based on the Lyapunov stability analysis, the sliding mode control methodology and the H ∞ control technique so that the stability of the closed-loop system and H ∞ tracking performance can be guaranteed. Finally, the proposed control system is applied to control an inverted pendulum system, a Van der Pol oscillator and a Genesio chaotic system. Simulation results demonstrate that the proposed control scheme can achieve favorable tracking performances for the uncertain nonlinear systems with unknown dynamic functions and under the occurrence of external disturbance. [Copyright &y& Elsevier]

Abstract: In this paper, adaptive control is studied for a class of single-input–single-output (SISO) nonlinear discrete-time systems in strict-feedback form with nonparametric nonlinear uncertainties of the Lipschitz type. To eliminate the effect of the nonparametric uncertainties in an unmatched manner, a novel future states prediction is designed using states information at previous steps to compensate for the effect of uncertainties at the current step. Utilizing the predicted future states, constructive adaptive control is developed to compensate for the effects of both parametric and nonparametric uncertainties such that global stability and asymptotical output tracking is achieved. The effectiveness of the proposed control law is demonstrated in the simulation. [Copyright &y& Elsevier]

• The exponential decay function is proposed as the reference model to guarantee speed error decay rapidly to zero. • By introducing the estimation of unknown disturbance boundary in the control law and the robust term in the updating law of parameter, the robustness is improved. • The convergence parameters are adjusted to improve the adaptive speed of parameters. • The steering load disturbances are divided into predictable time-varying term and bounded unknown time-varying disturbances to reduce the scope of uncertainty. Ensuring passenger comfort in steering process of autonomous vehicles is a key issue in corresponding product development. However, the existing steering control system has an inability to plan steering speed, which will increase the discomfort of passengers. In this paper, a novel reference model based adaptive control tactic is proposed to regulate steering speed of automatic steering system (ASS). In order to improve the response speed and control accuracy of ASS, firstly, exponential decay function is creatively proposed as a reference model to control the decay rate of the speed error of steering motor. Subsequently, to reduce the system uncertainty range, the steering load disturbance is treated as a known time-varying term and a bounded unknown time-varying disturbance. In order to compensate the uncertainties of nonlinear system, the additional estimation of disturbance boundary and the robust term in the parameters updating law are introduced. Besides, the stability and robustness of the whole system are verified by Lyapunov theory. Finally, simulation and HIL test results demonstrate the proposed control tactic ensures the tracking performance of steering speed control and the robust stability in the bounded unknown time-varying disturbance, which provides benefit reference for ASS development in practice. [ABSTRACT FROM AUTHOR]