Robust predictive sliding mode control for input rate-constrained discrete-time system

This paper is concerned with the robustness and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control problem of observer-based control for a class of uncertain linear discrete-time systems with both state and input delays. Under no disturbance input, the asymptotic stabilization for uncertain time-delay systems will be guaranteed. Linear Matrix Inequality(LMI) optimization approach is used to design the observer-based H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control. An example illustrates the application of the proposed technique.

In this paper, the finite-horizon near optimal adaptive regulation of linear discrete-time systems with unknown system dynamics is presented in a forward-in-time manner by using adaptive dynamic programming and Q-learning. An adaptive estimator (AE) is introduced to relax the requirement of system dynamics, and it is tuned by using Q-learning. The time-varying solution to the Bellman equation in adaptive dynamic programming is handled by utilizing a time-dependent basis function, while the terminal constraint is incorporated as part of the update law of the AE. The Kalman gain is obtained by using the AE parameters, while the control input is calculated by using AE and the system state vector. Next, to relax the need for state availability, an adaptive observer is proposed so that the linear quadratic regulator design uses the reconstructed states and outputs. For the time-invariant linear discrete-time systems, the closed-loop dynamics becomes non-autonomous and involved but verified by using standard Lyapunov and geometric sequence theory. Effectiveness of the proposed approach is verified by using simulation results. The proposed linear quadratic regulator design for the uncertain linear system requires an initial admissible control input and yields a forward-in-time and online solution without needing value and/or policy iterations. Copyright © 2014 John Wiley & Sons, Ltd.

This paper investigates the predictive sliding mode control problem of networked control system with long-time delay and consecutive packet dropout in both sensor-controller link and controller-actuator link. A new modeling method that uses only one Markov chain to describe the time delay and packet dropout in a unified model is proposed. As a modification of the original law, a new chattering-free reaching law that is suitable for multiple-input systems is proposed and is later used as the reference trajectory of the designed predictive sliding mode controller. To overcome the influence of time delay and packet dropout, a novel predictive sliding mode controller equipped with a logic zero-order-holder and delay compensator is proposed, and the proposed compensation strategy is theoretically proven to be able to make the system completely free from the influence of long-time delay and consecutive packet dropout. Finally, a simulation example is given to illustrate the validity of the proposed controller.

In order to effectively suppress horizontal vibration of the ultra-high-speed elevator car system. Firstly, considering the nonlinearity of guide shoe, parameter uncertainties, and uncertain external disturbances of the elevator car system, a more practical active control model for horizontal vibration of the 4-DOF ultra-high-speed elevator car system is constructed and the rationality of the established model is verified by real elevator experiment. Secondly, a predictive sliding mode controller based on adaptive fuzzy (PSMC-AF) is proposed to reduce the horizontal vibration of the car system, the predictive sliding mode control law is achieved by optimizing the predictive sliding mode performance index. Simultaneously, in order to decrease the influence of uncertainty of the car system, a fuzzy logic system (FLS) is designed to approximate the compound uncertain disturbance term (CUDT) on-line. Furthermore, the continuous smooth hyperbolic tangent function (HTF) is introduced into the sliding mode switching term to compensate the fuzzy approximation error. The adaptive laws are designed to estimate the error gain and slope parameter, so as to increase the robustness of the system. Finally, numerical simulations are conducted on some representative guide rail excitations and the results are compared to the existing solution and passive system. The analysis has confirmed the effectiveness and robustness of the proposed control method.

This paper considers a subclass of hybrid systems, which is the discrete-time linear switching systems whose changes in the dynamics are determined by exogenous, uncontrollable events, and resets are present. In the presence of uncertain parameter and non-symmetrical constrained control, based on the results of nominal linear switching systems, a necessary and sufficient condition to test the robustness of a state feedback controller is given. The candidate state feedback controller for this test is that stabilizing nominal discrete-time linear switching systems. Also, the method in this paper can be extended to the case which has state constraints. At last, a numerical example is presented to illustrate the technique.

In this paper, the Bellman equation is used to solve the optimal adaptive control of quantized linear discrete-time system with unknown dynamics. To mitigate the effect of the quantization errors, the dynamics of the quantization error bound and an update law for tuning the range of the dynamic quantizer are derived. Subsequently, by using adaptive dynamic programming technique, the infinite horizon optimal regulation problem of the uncertain quantized linear discrete-time system is solved in a forward-in-time manner without using value and/or policy iterations. The asymptotic stability of the closed-loop system is verified by standard Lyapunov stability approach in the presence of state and input quantizers. The effectiveness of the proposed method is verified via simulation.

In this paper, a class of discrete-time uncertain linear hybrid systems, which is affected by both parameter variations and exterior disturbances, is considered. The goal here is to synthesize a hybrid control law, which includes the continuous variable control law and the discrete event control signal, so as to guarantee the controlled invariance for a specific region in the hybrid state space. It turns out that the continuous variable control law is a piecewise linear state feedback control based on the partition of the given region's continuous variable state space projection. A numerical example is given for illustration.

A technique to design stabilizing state feedback controllers is presented for linear discrete-time systems subject to possibly time-varying parametric uncertainties. Conditions imposed on the uncertainties are less stringent than those found in the cited literature. The controller design procedure is based on the solution of a Riccati-like algebraic matrix equation. Stability considerations rely on the second method of Lyapunov, To evaluate the system's performance degradation due to uncertainty, an upper bound (guaranteed cost) is derived for the cost of the controlled uncertain system with respect to a designer chosen quadratic cost function. Two examples are given.

H∞ control of discrete-time uncertain linear systems with quantized feedback

An adaptive control framework for stabilization of 1-dimensional linear uncertain discrete-time dynamical systems with symbolic feedback is developed. The plant output is assumed to be quantized and only its symbolic quantity is fed back to the controller. In the case of multi-dimensional systems, ideal system matrix is constructed so that the approach for the scalar systems can be applied in separate subspaces in the state space.

A novel disturbance rejection control scheme is proposed to address the robust attitude control problem for the air-breathing hypersonic vehicle with actuator dynamics and disturbances based on predictive sliding mode control and nonlinear disturbance observer. To achieve attitude control subtly and precisely, the attitude control system is decomposed into two subsystems: the outer-loop subsystem and inner-loop subsystem. Different control schemes are taken to attenuate or reject model uncertainties and external disturbances, whose influences on the two subsystems are different. The predictive sliding mode control is first utilized to attenuate model uncertainties imposed on the outer-loop subsystem. Then, a novel nonlinear disturbance observer–based predictive sliding mode control is proposed to tackle the mismatched disturbances with remarkable influence on the inner-loop subsystem. Afterward, both the effectiveness and stability of the proposed nonlinear disturbance observer–based predictive sliding mode control disturbance rejection control scheme are demonstrated from the theoretical prospective. Finally, simulation results are given to present the effectiveness and robustness of the proposed disturbance rejection control scheme.

A sliding mode predictive control (SMPC) scheme integrated with an extreme learning machine (ELM) disturbance observer is proposed for the trajectory tracking of a flexible air-breathing hypersonic vehicle (FAHV). To streamline the controller design, the longitudinal model is decoupled into a velocity subsystem and an altitude subsystem. For the velocity subsystem, a proportional-integral sliding mode surface is designed, and the control law is derived by minimizing a cost function that weights the predicted sliding mode surface and the control input. For the altitude subsystem, a backstepping control framework is adopted, with the SMPC strategy embedded in each step. Multi-source disturbances are modeled as composite additive disturbances, and an ELM-based neural network observer is constructed for their real-time estimation and compensation, thereby enhancing system robustness. The semi-globally uniformly ultimately bounded (SGUUB) stability of the closed-loop system is rigorously proven using Lyapunov stability theory. Simulation results demonstrate the comprehensive superiority of the proposed method: it achieves reductions in Root Mean Square Error (RMSE) of 99.60% and 99.22% for velocity and altitude tracking, respectively, compared to Prescribed Performance Control with Backstepping Control (PPCBSC), and reductions of 98.48% and 97.12% relative to Terminal Sliding Mode Control (TSMC). Under parameter uncertainties, the developed ELM observer outperforms RBF-based observer and Extended State Observer (ESO) by significantly reducing tracking errors. These findings validate the high precision and strong robustness of the proposed approach.

This paper studies the design of uncertain linear discrete-time Networked Control Systems over imperfect communication channels with time-varying data loss. This leakage is modeled as stochastic parameter and norm-bounded uncertainties. In addition, this paper defines the necessary conditions for the design of the dynamic output feedback controller; subsequently, an iterative LMI approach is specified to compute the controller state parameters. The simulation results show that the designed controller improves the H∞ disturbance attenuation performance of the concerned uncertain system.

The authors present a sufficient condition for quadratic stabilizability of uncertain linear discrete time systems using LQ (linear quadratic) regulators. The true system is represented by a nominal model plus additive terms representing the uncertainties in the state and input matrices. With a proper choice of these terms, one may represent the most common types of uncertainties encountered in the literature. The main result of the present work is a robustification procedure for discrete time LQ regulators, which is based on a sufficient condition for quadratic stabilizability. The conservativeness of the proposed condition is discussed and some examples are given. >

This paper studies the simultaneous fault detection and control problem for linear uncertain discrete-time systems. A design procedure dealing with polytopic uncertainties is proposed for residual generation, where both the fault detection objectives and some control objectives are considered simultaneously through certain performance indexes. To cope with the fault sensitivity performance index in a given frequency range directly, the generalised KYP lemma is introduced in this framework. A two-step procedure is adopted to obtain the solutions through satisfying a set of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed methods.