Anti-Disturbance Output Feedback Tracking Control for Switched Stochastic Systems With Multiple Disturbances via Mode-Dependent Average Time Method

In complex industrial situations, modern permanent magnet synchronous motor (PMSM) servo drive system always face different kinds of disturbances, especially constant or slowly-varying disturbances (load disturbances) and periodic disturbances (torque ripples). Conventional disturbance rejection techniques, e.g., the extended state observer based control (ES-OBC) and the disturbance observer based control (DOBC), can only reject asymptotically single kind of disturbances (constant or slowly-varying disturbances). To this end, it is essential to extend the conventional disturbance rejection approach for multiple disturbances. Inspired by the internal model principle (IMP), appropriately embedding the model of disturbances into the design of disturbance observer, a composite disturbance observer based control is proposed for PMSM with multiple disturbances. The proposed disturbance observer (named as IMESO), consisting of the internal model principle (IMP) and the extended state observer (ESO), can reject multiple disturbances asymptotically. Thus, a composite control law consisting of proportional feedback and disturbance feedforward compensation is developed to control the speed loop. The proposed method is effective to reject the intricate multiple external disturbances and unmodeled dynamics. Simulations and experiments both verify the effectiveness of the proposed method.

This paper deals with the global output feedback tracking control problem for a class of switched nonlinear systems involving unknown parameters and unmeasured states multiplied by output nonlinearities. The switching information is assumed to be unobservable. To approach this purpose, a modified high-gain observer is introduced, and then an adaptive output feedback controller is constructed by adopting the adaptive backstepping technique. It is shown that, under arbitrary switching the proposed controller can guarantee all signals of the closed-loop system are globally uniformly bounded and the tracking error converges to a residual set that can be made arbitrarily small by properly selecting the design parameters. Simulation results are presented to verify the effectiveness of the proposed approach.

Adaptive disturbance rejection neural output feedback control of hydraulic manipulator systems

International audience

This paper mainly focuses on output feedback practical tracking controller design for stochastic nonlinear systems with polynomial function growth conditions. Mostly, there are some studies on output feedback tracking control problem for general nonlinear systems with parametric certainty in existing achievements. Moreover, we extend it to stochastic nonlinear systems with parametric uncertainty and system nonlinear terms are assumed to satisfy polynomial function growth conditions which are more relaxed than linear growth conditions or power growth conditions. Due to the presence of unknown parametric uncertainty, an output feedback practical tracking controller with dynamically updated gains is constructed explicitly so that all the states of the closed-loop systems are globally bounded and the tracking error belongs to arbitrarily small interval after some positive finite time. An example illustrates the efficiency of the theoretical results.

SUMMARYThis paper aims to propose an additive‐state‐decomposition‐based tracking control framework, based on which the output feedback tracking problem is solved for a class of nonminimum phase systems with measurable nonlinearities and unknown disturbances. This framework is to ‘additively’ decompose the output feedback tracking problem into two more tractable problems, namely an output feedback tracking problem for a linear time invariant system and a state feedback stabilization problem for a nonlinear system. Then, one can design a controller for each problem respectively using existing methods, and these two designed controllers are combined together to achieve the original control goal. The main contribution of the paper lies on the introduction of an additive state decomposition scheme and its implementation to mitigate the design difficulty of the output feedback tracking control problem for nonminimum phase nonlinear systems. To demonstrate the effectiveness, an illustrative example is given. Copyright © 2013 John Wiley & Sons, Ltd.

A bounded controller is proposed for a class of uncertain discrete time-delay systems with nonlinearity and disturbance based on state estimator and disturbance observer technique. A state estimator is developed to estimate the unmeasured system state vector. Suppose that the disturbance is generated by an exogenous system; a disturbance observer is designed to estimate the unknown disturbance. The parameters of the state estimator and the disturbance observer are calculated by solving linear matrix inequalities (LMIs). By applying the outputs of the state estimator and the disturbance observer, the sufficient condition for the existence of the bounded controller is derived based on an appropriate Lyapunov function candidate. Under the developed bounded controller, the stability of the closed-loop system can be guaranteed. Simulation examples are provided to show the effectiveness of the proposed bounded control scheme.

This paper investigates the exponential stability problem for a class of stochastic neural networks with leakage delay. By employing a suitable Lyapunov functional and stochastic stability theory technic, the sufficient conditions which make the stochastic neural networks system exponential mean square stable are proposed and proved. All results are expressed in terms of linear matrix inequalities (LMIs). Example and simulation are presented to show the effectiveness of the proposed method.

A quadrotor unmanned aerial vehicle (UAV) must achieve desired flight missions despite internal uncertainties and external disturbances. This paper proposes an adaptive trajectory tracking control method that attenuates unknown uncertainties and disturbances. Although the quadrotor is underactuated, a fully actuated controller is designed using backstepping control. To avoid repeated derivatives of control inputs, a dynamic surface method introduces a filter and auxiliary controller. Lyapunov criteria guide adaptive laws for tuning controller gain and filters. A low-power observer is integrated for state estimation. Additionally, a disturbance observer is developed and combined with the control scheme to handle unknown disturbances. Simulations on a DJI F450 quadrotor demonstrate that the proposed control algorithm offers strong trajectory-tracking performance and system stability under multiple uncertainties and external disturbances during flight.

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.

Mean square exponential stability of stochastic genetic regulatory networks with time-varying delays

In this article, for a class of uncertain nonlinear systems, an adaptive predefined‐time output feedback tracking control problem is investigated. Both the input signal and the output signal of the system are quantized for the sake of a lighter communication burden. First of all, a dynamic filtering technology is applied to overcome the virtual control signals being directly differentiated. Secondly, a well‐constructed observer powered by quantized output and input is devised, which can help resolve the difficulty of immeasurable states. Thirdly, an adaptive output feedback control scheme is put forward under the backstepping design framework. Compared with the current predefined‐time design methods, the adaptive law designed in this paper is expressed as a nonlinear differential equation, which ensures the predefined‐time stability. It is shown that all the signals in a predefined time interval are bounded and the controlled system is practically predefined‐time stable (PPTS). Ultimately, the effectiveness of the suggested control algorithm is illustrated through two examples.

In this study, a simple decentralized H$$ _{\infty} $$ fault-tolerant observer-based proportional-integral-derivative formation tracking design is proposed for network control systems of large-scale low earth orbit satellites under external disturbance, coupling and malicious attack signals via wireless communication channels. First, a novel reference-based feedforward linearization control scheme is introduced, transforming the nonlinear formation output feedback tracking control problem into an equivalent linearized formation tracking control system of each satellite. To prevent faults from corrupting the estimation and control of the satellite formation, two novel smoothing models of actuator and sensor fault signals are embedded in the equivalent linearized formation system of each satellite. Then, a decentralized H$$ _{\infty} $$ fault-tolerant observer-based proportional-integral-derivative control strategy is proposed to efficiently attenuate the effect of actuator and sensor faults, measurement noise and satellite coupling on the overall team formation. We only need to solve a linear matrix inequality-constrained optimization problem for each satellite to achieve the optimal H$$ _{\infty} $$ formation problem. Finally, a team formation example with twelve satellites crossing four orbits for a specific mission is provided to validate the proposed design, comparing it with other methods.

This paper investigates the composite hierarchical anti‐disturbance control problem for switched systems with saturating inputs, in which the multiple disturbances including normal‐bounded disturbances, white noises and nonlinear uncertainties are considered. According to whether the states of the system be available or not, two types of disturbance observers and a state observer are designed, respectively. With the values of the observers, the observer‐based composite controllers are constructed accordingly, under which an uniform form of the closed‐loop system is presented. By utilising the minimum dwell‐time technique and stochastic control theory, a new criterion of the mean‐square exponential stability is presented for the closed‐loop system with a weighted performance level. The design conditions of the observers for the disturbances generated by exosystem and states of the system are proposed by propositions, respectively. Based on the gains of the observers, the solvable synthesis conditions of the composite controllers are presented for the cases of the available and unavailable states of the system. The simulations of GE‐90 aero‐engine model and a numerical example are employed to verify the applicability of the obtained results.

SummaryThis paper is concerned with the analysis of the mean square exponential stability and the almost sure exponential stability of linear stochastic neutral delay systems. A general stability result on the mean square and almost sure exponential stability of such systems is established. Based on this stability result, the delay partitioning technique is adopted to obtain a delay‐dependent stability condition in terms of linear matrix inequalities (LMIs). In obtaining these LMIs, some basic rules of the Ito calculus are also utilized to introduce slack matrices so as to further reduce conservatism. Some numerical examples borrowed from the literature are used to show that, as the number of the partitioning intervals increases, the allowable delay determined by the proposed LMI condition approaches hmax, the maximal allowable delay for the stability of the considered system, indicating the effectiveness of the proposed stability analysis. Copyright © 2013 John Wiley & Sons, Ltd.