Influence Of Unknown Disturbances Research Articles

Cascade multi-resonant disturbance observer design. Application to a distillation column

In this work, we present a novel approach for input disturbance estimation design and implementation for dynamical processes under the influence of unknown disturbances that present a clear periodical behaviour of a known frequency. Both the design and the implementation are focused on simplicity. The observer consists of a set of transfer functions fed by the process manipulated variable and the sensor measurement that are implemented through a mixture of cascade and series connections. For the synthesis of the disturbance observer, we just need an input–output model of the process and one tuning parameter in each of the transfer functions. We present simple rules for the design considering the trade-off between the transient time needed to estimate changes in the behaviour of the disturbance and the robustness against measurement noise effects. We show the benefits in using this disturbance estimation as a feed-forward signal in both open loop and closed loop control applications, and we quantify the robustness modification when used together with a closed loop controller. The transfer functions of the observer include both a low pass filter and a set of resonant terms. We quantify the effect of the different terms and their parameter tuning. Our implementation method uses standard tools available in industrial control systems and we have applied it to a real distillation column under ambient temperature disturbances. The main contribution of this work is the simplicity of the design and implementation of the disturbance observer, making it suitable for the process industry and to be managed by non-experts in control systems. Another contribution is the a priori design based in intuitive engineering performance indices.

Quantized control for switched systems suffered by deception attacks and unknown disturbance

AbstractThe purpose of this paper is designing a feedback controller based on quantized sampled data to stabilize a continuous‐time switched system affected by unknown disturbance and deception attacks. Suppose that the switch is slow enough in the sense of dwell‐time and average dwell‐time, and the attacker's energy is limited by restraining the number and duration of deception attacks, we design a communication and control strategy based on mode switching and data tampering. By approximating the reachable set for the stabilizing stage and searching stage, respectively, we establish the increasing/decreasing rate of Lyapunov function under different cases. On this basis, the sufficient conditions which constrain average dwell‐time and sampling period are obtained to ensure the exponential decay and practical stability of the closed‐loop system. Furthermore, we also verify that the searching stage can be recovered within an unknown limited time under the influence of unknown disturbance and deception attacks. Two‐tank system is adopted at last to show the effectiveness of the proposed algorithm framework.

Adaptive integral-sliding-mode control strategy for maneuvering control of F16 aircraft subject to aerodynamic uncertainty

Aircraft dynamics are highly nonlinear and the traditional linear flight controllers cannot fully utilize the real-time performance ability of aircraft. This paper investigates a nonlinear control approach for high maneuvering fighter aircraft that deployed baseline nonlinear-dynamics-inversion (NDI) control and high-level robust adaptive integral-sliding-mode (ISM) control. The design objective is to maintain the acceptable flight quality at a high angle-of-attack under the influence of unknown disturbance and aerodynamics uncertainties. The nonlinear dynamics of F16 aircraft are divided into two loops by utilizing time-scale separation principle and adaptive ISM/NDI controller is designed for each loop. The aerodynamics coefficients are estimated using the iterative reweighted least square (IRLS) algorithm based on the wind tunnel real-time flight data available at NASA Langlet and Ame Research center. The internal dynamics stability is proven to validate the complete system stability. Simulations are conducted on F16 aircraft and compared the results with the NDI controller and ISM/NDI controller (without adaptive strategy).

Adaptive output feedback boundary control for a class of axially moving system

In this study, the main concern lies in the development of a boundary control scheme for suppressing the vibration of an axially moving system under the influence of unknown disturbances. To that end, a boundary adaptive output feedback control is presented by merging Lyapunov theory, observer backstepping technique, high-gain observers and robust adaptive control theory to globally stabilise the vibration and compensate for the uncertainties of the system. Besides, the disturbance observer dynamics is developed to handle unknown boundary disturbance and the σ -modification is adopted to adjust the robustness of the system. Under the designed control, the uniformly bounded stability of the controlled system is achieved, and the state observer error exponentially converges to zero as time tends to infinity. Simulation results illustrate that the proposed control can stabilise the system with a better performance.

Fault detection for discrete-time Lipschitz nonlinear systems with signal-to-noise ratio constrained channels

In this paper, the problem of fault detection for discrete-time Lipschitz nonlinear systems with additive white Gaussian noise channels subject to signal-to-noise ratio constraints is investigated. An optimal residual generator based on the mixed H−/H∞ performance index is designed to generate the so-called residual signal, and the H−-index is used to measure the minimum effect of faults on the residual signal, while the influence of unknown disturbances and channel noise on the residual signal is maximized by the means of the H∞-index. Then, in order to detect the occurrence of faults, a norm-based residual evaluation function is provided, and a dynamic threshold including upper bounds on the modulus of the solution of Lipschitz nonlinear systems and the stochastic properties of channel noise is also constructed. Finally, a simulated example is presented to demonstrate the effectiveness of the proposed approach.

Fault detection for a class of Markov jump systems with unknown disturbances

An optimized fault detection observer is designed for a class of Markov jump systems with unknown disturbances. By reconstructing the system, the residual error dynamic characteristics of unknown input and fault signals, including unknown disturbances and modeling error are obtained. The energy norm indexes of disturbance and fault signals of the residual error are selected separately to reflect the restraint of disturbance and the sensitivity of faults, and the design of the fault detection observer is described as an optimization problem. By using the constructed Lyapunov function and linear matrix inequalities, a sufficient condition that the solution to the fault detection observer exists is given and proved, and an optimized design approach is presented. The designed observer makes the systems have stochastic stability and better capability of restraining disturbances, and the given norm index is satisfied. Simulation results demonstrate that the proposed observer can detect the faults sensitively, and the influence of unknown disturbance on residual error can be restrained to a given range.

Trajectory linearization control of an aerospace vehicle based on RBF neural network

An enhanced trajectory linearization control (TLC) structure based on radial basis function neural network (RBFNN) and its application on an aerospace vehicle (ASV) flight control system are presensted. The influence of unknown disturbances and uncertainties is reduced by RBFNN thanks to its approaching ability, and a robustifying item is used to overcome the approximate error of RBFNN. The parameters adaptive adjusting laws are designed on the Lyapunov theory. The uniform ultimate boundedness of all signals of the composite closed-loop system is proved based on Lyapunov theory. Finally, the flight control system of an ASV is designed based on the proposed method. Simulation results demonstrate the effectiveness and robustness of the designed approach.

Robust control of discretized continuous systems using the theory of sliding modes

The idea of sliding mode control (SMC) as a robust control technique is utilized to control systems where the dynamics can be described by [xdot](t) = (A + ΔA)x(t) + (B + ΔB)u(t) + d(t) where ΔA, ΔB and d(t) characterize unknown plant parameters and unexpected disturbances, respectively. The analysis is described in the discrete form using the Euler operator. The proposed controller regards the influence of unknown disturbances and parameter uncertainties as an equivalent disturbance and generates a control function (estimate) to cancel their influence by the mechanism of time delay, The states of the uncertain plant are steered from an arbitrary initial state to a stable surface, s = 0, and the plant output is subsequently regulated. One feature of the control is that the sliding conditions are satisfied without the discontinuous control action used in classical SMC. It therefore retains the positive features of SMC without the disadvantage of control chattering. The controller has been studied through simulations and experiment on an NSK direct drive robot arm driven by a DC motor. The results confirm that the control is robust to disturbances and parameter variations.

Modeling Hubble Space Telescope flight data by Q-Markov cover identification

This Paper presents a state space model for the Hubble space telescope under the influence of unknown disturbances in orbit. This model was obtained from flight data by applying the Q-Markov Covariance Equivalent Realization identification algorithm. This state space model guarantees the match of the first Q Markov parameters and covariance parameters of the Hubble system. The flight data were partitioned into high and low frequency components for more efficient Q-Markov Cover modeling, to reduce some computational difficulties of the Q-Markov Cover algorithm. This identification revealed more than 20 lightly-damped modes within the bandwidth of the attitude control system. Comparisons with the analytical (TREETOPS) model are also included.