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Abstract: The problem of process systems subject to actuator faults (partial loss of actuator effectiveness) is considered. An active fault compensation control law is designed that utilizes compensation in a way that accounts for matching and unmatching uncertainties and the occurrence of actuator faults. The main idea is designing the robust compensation controller to guarantee closed-loop stability in the presence of faults, based on a neural network representation of the fault dynamics. Changes in the system due to faults are modeled as unknown nonlinear functions. The updating control law is derived such that all the parameters of the closed-loop system are bounded. An output feedback controller is used to the “healthy” system and the adaptive feedback controller is used to compensate for the effect of the dynamics caused by the fault. The advantage of fault compensation is the dynamics caused by faults can be accommodated online. The proposed design method is illustrated on a three-tank system. [Copyright &y& Elsevier]

Abstract-A robust adaptive control approach is proposed to solve the consensus problem of multiagent systems. Compared with the previous work, the agent's dynamics includes the uncertainties and external disturbances, which is more practical in real-world applications. Due to the approximation capability of neural networks, the uncertain dynamics is compensated by the adaptive neural network scheme. The effects of the approximation error and external disturbances are counteracted by employing the robustness signal. The proposed algorithm is decentralized because the controller for each agent only utilizes the information of its neighbor agents. By the theoretical analysis, it is proved that the consensus error can be reduced as small as desired. The proposed method is then extended to two cases: Agents form a prescribed formation, and agents have the higher order dynamics. Finally, simulation examples are given to demonstrate the satisfactory performance of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we establish the robustness of adaptive controllers designed using the standard backstepping technique with respect to unmodeled dynamics involving unknown input time delay. While noting that some results on robust stabilization of non-minimum phase systems using the backstepping technique are available, we realize that the standard adaptive backstepping technique has only been shown applicable to unknown minimum phase systems. Another significance of our result is to enable the class of systems stablizable by adaptive backstepping controllers to cross the boundary of minimum phase systems, since systems with input time delay belong to non-minimum phase systems. Moreover, the and norms of the system output are also established as functions of design parameters. This implies that the transient system performance can be adjusted by choosing suitable design parameters. [Copyright &y& Elsevier]

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]

In this paper, we study the limitations of the capability of the feedback mechanism in dealing with structural uncertainty for a class of pth order non-linear autoregressive control systems. The size of the structural uncertainty is characterized by multiple Lipschitz constants (say L1,L2,...,Lp) of the uncertain non-linear function. It is shown that if L1,L2,...,Lp satisfy certain algebraic conditions, then there exists no globally stabilizing feedback control law for the corresponding uncertain systems. The result here is an extension of the previous result obtained by Zhang and Guo (2002). [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]