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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]

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]

In this article, we are dedicated to coping with the control design for underactuated mechanical system (UMS) with system uncertainties, which is also subject to a set of servo constraints. For the nominal system without any initial condition deviations, this article provides a general model-based servo control with the idea of second-order constraints, which can be derived from both holonomic and nonholonomic ones. For the uncertain system, with the uncertainties being separated into matched portions and mismatched portions, this article provides an adaptive robust control scheme to guarantee the UMS to attain the deterministic performance on the basis of nominal control. The leakage-type adaptive law is to size up the unknown uncertainty bounds. The cart-pole system and the rotational-translational actuator system are used to verify the availability of the proposed adaptive robust control. [ABSTRACT FROM AUTHOR]

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

An optimal control design for the uncertain Delta robot is proposed in the paper. The uncertain factors of the Delta robot include the unknown dynamic parameters, the residual vibration disturbances and the nonlinear joints friction, which are (possibly fast) time-varying and bounded. A fuzzy set theoretic approach is creatively used to describe the system uncertainty. With the fuzzily depicted uncertainty, an adaptive robust control, based on the fuzzy dynamic model, is established. It designs an adaptation mechanism, consisting of the leakage term and the dead-zone, to estimate the uncertainty information. An optimal design is constructed for the Delta robot and solved by minimizing a fuzzy set-based performance index. Unlike the traditional fuzzy control methods (if-then rules-based), the proposed control scheme is deterministic and fuzzily optimized. It is proven that the global solution in the closed form for this optimal design always exists and is unique. This research provides the Delta parallel robot a novel optimal control to guarantee the system performance regardless of the uncertainty. The effectiveness of the proposed control is illustrated by a series of simulation experiments. The results reveal that the further applications in other robots are feasible. [ABSTRACT FROM AUTHOR]

This note investigates the dynamic positioning control problem of full-actuated marine vehicles in the presence of system uncertainties and input constraints. In the control algorithm, the ship model uncertainty is approximated by the radial-basis-function neural networks. The effect of input saturation is analyzed by the auxiliary system, states of the auxiliary system are employed to develop the control scheme. By virtue of the dynamic surface control technique, the inherent problem of "explosion of complexity" problem occurred during conventional Backstepping design framework is avoided. The semi-global uniformly ultimately bounded stability of the closed-loop is guaranteed by Lyapunov theory. Since the minimal learning parameterization based adaptive law is derived, the number of parameters updated online is reduced to 6. Consider the servo-system uncertainty, the control inputs of interest are achieved as the measurable propeller pitch whose characteristics would facilitate the implementation of the algorithm in the practical engineering. Finally, by employing a supply vessel as the plant, comparison simulations are conducted to demonstrate the effectiveness and robustness of the proposed algorithm. [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]

Motion control for an uncertain swarm robot system consisting of N robots is considered. The robots interact with each other through attractions and repulsions, which mimic some biological swarm systems. The uncertainty in the system is possibly fast time varying and bounded with unknown bound, which is assumed to be within a prescribed fuzzy set. On this premise, an adaptive robust control is proposed. Based on the proposed control, an optimal design problem under the fuzzy description of the uncertainty is formulated. This optimal problem is proven to be tractable, and the solution is unique. The solution to this optimal problem is expressed in the closed form. The performance of the resulting control is twofold. First, it assures the swarm robot system deterministic performances (uniform boundedness and uniform ultimate boundedness) regardless of the actual value of the uncertainty. Second, the minimization of a fuzzy-based performance index is assured. Therefore, the optimal design problem of the adaptive robust control for fuzzy swarm robot systems is completely solved. [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]

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 studies relative pose control for a rigid spacecraft with parametric uncertainties approaching to an unknown tumbling target in disturbed space environment. State feedback controllers for relative translation and relative rotation are designed in an adaptive nonlinear robust control framework. The element-wise and norm-wise adaptive laws are utilized to compensate the parametric uncertainties of chaser and target spacecraft, respectively. External disturbances acting on two spacecraft are treated as a lumped and bounded perturbation input for system. To achieve the prescribed disturbance attenuation performance index, feedback gains of controllers are designed by solving linear matrix inequality problems so that lumped disturbance attenuation with respect to the controlled output is ensured in the L 2 -gain sense. Moreover, in the absence of lumped disturbance input, asymptotical convergence of relative pose are proved by using the Lyapunov method. Numerical simulations are performed to show that position tracking and attitude synchronization are accomplished in spite of the presence of couplings and uncertainties. [ABSTRACT FROM AUTHOR]

This paper presents a novel robust control for electrically driven robot manipulators by designing an adaptive uncertainty estimator based on the first order Taylor series. The estimator is simple and model-free in a decentralized structure. The uncertainty is then efficiently compensated in the control system. The controller does not require the bounding functions as an advantage over the conventional robust controller. Therefore, it is simpler, less computational, and more efficient. It is verified by stability analysis and its effectiveness is shown through comparisons with a terminal sliding mode control approach and a Legendre polynomials uncertainty bound estimator simulated on a SCARA robot driven by permanent magnet dc motors. [ABSTRACT FROM AUTHOR]

• A cooperative robust non-fragile fault tolerant strategy for safety of the intended functionality of CACC with complex uncertainties. • An intermediate based cooperative robust estimation method is proposed to estimate the motion information and performance limitations of the platoon vehicles, simultaneously. • A distributed robust non-fragile fault tolerant H∞ control method is proposed to compensate the effects of performance limitations and uncertainties. • This research opens a path towards SOTIF of connected and autonomous vehicles by designing fault tolerant strategies. Safety of the intended functionality (SOTIF) of connected and autonomous vehicles (CAVs) is very challenging due to heterogeneous performance limitations and complex uncertainties in real road environments. In this paper, a cooperative robust non-fragile fault tolerant control (CRNFTC) strategy is presented to reduce the risks caused by multi-vehicle performance limitations of perception and actuation systems for ensuring SOTIF of cooperative adaptive cruise control (CACC). First, an intermediate based cooperative robust estimation method is proposed, by combining ego and cooperative information, system states, matched disturbances, performance limitations of perception and actuation of the vehicles in the platoon are simultaneously estimated. Existence conditions of estimators are given with respect to predecessor following (PF) and bi-directional (BD) communication network topologies. Then, based on the estimation, a distributed robust non-fragile fault tolerant H∞ control method is proposed, such that compensation of the effects of heterogeneous performance limitations and matched disturbances, and suppression of the remaining unmatched disturbances can be achieved. The sufficient condition and optimal solution of the proposed CRNFTC are obtained by using Lyapunov theory with explicit consideration of the system uncertainty and controller perturbation. The efficacy and superiority of the proposed CRNFTC for ensuring SOTIF of the CACC of PF and BD communication network topologies with complex uncertainties are substantiated via a series of simulations and quantitative comparisons. [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 provides a solution for the position tracking and attitude synchronization problem of the close proximity phase in spacecraft rendezvous and docking. The chaser spacecraft must be driven to a certain fixed position along the docking port direction of the target spacecraft, while the attitude of the two spacecraft must be synchronized for subsequent docking operations. The kinematics and dynamics for relative position and relative attitude are modeled considering dynamic coupling, parametric uncertainties and external disturbances. The relative motion model has a new form with a novel definition of the unknown parameters. An original robust adaptive control method is developed for the concerned problem, and a proof of the asymptotic stability is given for the six degrees of freedom closed-loop system. A numerical example is displayed in simulation to verify the theoretical results. [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 paper presents an attitude control problem of reusable launch vehicles in reentry phase. The controller is designed based on synthesizing robust adaptive control into backstepping control procedure in the presence of input constraint, model uncertainty, and external disturbance. In view of the coupling between the states of translational motion and the states of attitude motion, the control-oriented model is developed, where the uncertainties do not satisfy linear parameterization assumption. The time derivative of the virtual control input is viewed as a part of uncertain term to facilitate the analytic computations and avoid the 'explosion of terms' problem. The robust adaptive backstepping control scheme is first proposed to overcome the uncertainty and external disturbance. The robust adaptive law is employed to estimate the unknown bound of the uncertain term. Furthermore, the attitude control problem subjects to input constraint is studied, and the constrained robust adaptive backstepping control strategy is proposed. Within the Lyapunov theory framework, the stability analysis of the closed-loop system is carried out, and the tracking error converges to a random neighborhood around origin. Six-degree-of-freedom reusable launch vehicle simulation results are presented to show the effectiveness of the proposed control strategy. Copyright © 2015 John Wiley & Sons, Ltd. [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]

We develop a new adaptive gain-scheduling control scheme for continuous-time linear systems with polytopic uncertainties. The gain-scheduled control law is proposed as a convex sum of a fixed set of controller gains, exploiting the polytopic representation of the system uncertainty, which is not possible with classical robust control results in the literature. To realize this scheme, an adaptation law is proposed to adaptively provide the tuning parameter for the gain-scheduling implementation. The admissible domain of the stabilizing control feedback gains, defined by the fixed set of controller gains, can be determined offline by solving a set of linear matrix inequality constraints over a scalar line search. Using Lyapunov-based arguments, the proposed design conditions and the adaptation law ensure that all closed-loop signals are bounded. In particular, if the uncertain parameters are not time-varying, then the system states asymptotically converge to the origin. Theoretical arguments and appropriate numerical illustrations are provided to demonstrate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

• 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]