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This study elucidates a robust control scheme for pseudolinear systems that are subject to some uncertainties. Pseudolinear systems are nonlinear systems that are fully feedback linearizable. The system involves robust pole assignment (RPA) control, quasi-similarity transformation (QST), and approximate feedback linearization (AFL). First, using the results of exact feedback linearization (EFL), we...
Disturbance Feedback Control (DFC) is a control technique that augments robustness of existing control systems with an extra feedback loop for the purpose of attenuation of disturbances and model errors. In this work, we propose a DFC design method based on output feedback control via Linear Matrix Inequalities (LMIs). A parametric uncertainty model is used to represent mismatches between a nominal...
This paper considers the robust consensus problem of Lipschitz nonlinear multi-agent systems with matched disturbances and time-delay dynamics. By LMI approach based on Lyapunov function, distributed adaptive protocols are proposed, which rely on the state information of neighbor agents. Theoretical analysis indicates that the proposed protocol achieve both the leaderless and leader-following consensus...
This paper deals with a robust formation control methodology for the Multi-UAV system with uncertain exogenous disturbance. The fourth-order UAV model with disturbance and the disturbance estimate system is introduced. In order to achieve the rigid formation fight, graph theory and consensus algorithm are utilized and the state of the UAVs converges to desired value by using Leader-Follower structure...
This paper presents a novel approach for an interval-based gain scheduling control design aiming at a guaranteed stabilization of the system dynamics over a predefined time horizon. Due to the goal of asymptotic stability, the design aims at the temporal reduction of the widths of intervals representing worst-case bounds of the system states at a specific point of time. The main idea of the control...
The paper discusses a novel probabilistic approach for online parameter estimation of the predictor model used in an MPC (Model Predictive Control) setting in the presence of model uncertainties and external disturbances. Model uncertainty makes it hard to compute an optimal control in general case, because it is needed to take into account all possible values of model parameters. Therefore, it is...
This paper studies the problem of high-precision positioning of laser beams by using a robust Fractional-Order Proportional-Integral-Derivative (FOPID) controller. The control problem addressed in laser beams aims to maintain the position of the laser beam on a Position Sensing Device (PSD) despite the effects of noise and active disturbances. The FOPID controller is well known for its simplicity...
This paper develops a non-monotonic Lyapunov function (LF) approach for discrete-time switching linear system with average dwell time (ADT) switching to improve the stability criterion and achieve better H∞ performance. Such an approach allows the LF to increase both at the switching instants and during the running time of subsystems, but guarantees an average decrease on every two sampling steps...
In this paper, we present a robust pole placement control scheme that can be used to control a wide class of linear and time invariant systems with unknown parameters, including nonminimum phase systems, using only plant input and output signals. We assume that the unknown plant parameters has known bounds, i.e., the control scheme is designed for an interval plant whose coefficients are closed intervals...
Model-based predictive control is an effective method for control the large scale systems. Method is based on on-lin solution of control task over the control horizon using current and past measurements as well as the system model. Because model and measurement uncertainty, predicted and plant outputs might be different and plant output may exceed plant output constraints. Generated control is not...
In this paper, the problem of adaptive fixed-time 6 degree-of-freedom (DOF) tracking control for spacecraft non-cooperative rendezvous in presence of the parameter uncertainties and external disturbances is investigated. Firstly, a new multilayer fixed-time sliding mode surface (MFSMS) is designed, and the setting time of the proposed surface can be estimated without the knowledge of the initial conditions...
A modular approach of the estimation-based design in the adaptive linear control systems has been extended to the adaptive robust control of strict-feedback stochastic nonlinear systems with additive standard Wiener noises and constant unknown parameters. Using Itô differentiation rule, nonlinear damping and adaptive Backstepping procedure, the disturbance-to-state stable controller of global stabilization...
This paper considers a robust control strategy for main steam temperature system of thermal power plant that is affected by immeasurable bounded disturbances. An output-feedback min-max optimization approach is proposed to obtain a controller which could effectively reject disturbances and stabilize the system. This approach combines moving horizon estimation with model predictive control and is formulated...
Robust adaptive time-varying formation control problems for high-order linear multi-agent systems with parameter uncertainties and external disturbances are investigated. Firstly, using the adaptive updating mechanism, a fully distributed time-varying formation control protocol is proposed. The protocol is determined by each agent in a fully distributed form and does not need any global information...
We exploit how to overcome phase damping decoherence when the phase damping parameters are uncertain. It is shown that the “relaxed” control goal may be achieved by combing simple open-loop coherent control with periodic projective measurements. Both the sufficient conditions and constructive design procedures are presented. The control design is reduced to selecting the period of projective measurements...
This paper proposes a robust iterative learning control method for the refining furnace alloy weighing process to solve the problem of the poor control accuracy and stability caused by the changing of alloy properties and the frequency of the vibration feeder. First, a two dimensional (2D) weighing model was established based on the analysis of the dynamic characteristics of alloy weighing process...
Small gain theorem is used to interpret stability and robustness of linear active disturbance rejection control(LADRC). For the case linear unmodeled dynamic and additive external disturbance, LADRC system is decomposed into two interconnected subsystems. The first subsystem includes all parametric uncertainty of the plant, while the second has a gain which can be adjusted by choosing the parameters...
Further research based on the author's past work in [1] is performed in this paper. A structural robust gain-scheduled (GS) PID control method is proposed and applied to control the pitch angle for a morphing wing UAV(MUAV) in its transient process. Firstly, the author gives the robust static output feedback (SOF) control method for LPV system and shows that PID control is equivalent to SOF control,...
For the strict-feedback systems with disturbances, a novel robust control is proposed based on dissipation theory in this article. By combining the techniques of feedback linearization and feedback domination, the nonlinear controller is constructed step by step, where the notions of supply rate and storage function are embedded. The gotten robust controller makes the closed-loop system finite-gain...
In this paper, Maclaurin expansion and Padé approximation are utilized to handle the RHP zeros in the simplified decoupling control and the choosing strategy is given. To improve the robustness of each loop, Active Disturbance Rejection Control (ADRC) is adopted as a good solution which can estimate and compensate the total disturbances by the extended state observer (ESO). Besides, the stability...
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