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1.
This study presents an output backstepping control architecture based on command filter via Multilayer-Neural-Network Pre-Observer with compensator to realise the reference signal tracking of an arbitrarily switching nonlinear systems with nonseperated parameter. First, a multilayer neural network pre-observer is designed before backstepping procedures to servo reconstruct the system states which can not be obtained directly. The pre-observer has superior performance in neutralizing the states abrupt chattering caused by the arbitrarily switching parameter entered in the nonlinear structure. Next, observer error compensation mechanism is designed to compensate the state estimation and shrink the approximation error domain further. Then, the backstepping controller with compensation signal based on command filter is presented to realise the stable reference signal tracking. Last, the proposed control scheme guarantees the states of the closed-loop system bounded. This mechanism makes up the shortcoming of the traditional state observer and give more flexibility in reconstructing the systems states timely, then overcomes the obstacle of the arbitrarily switching parameterized system. Furthermore, compared with the existing traditional uniform robust uncertain controller, the developed backstepping control method combining with the pre-observer not only guarantees the states servo reconstruction and servo control of the switched system, but also improves the tracking performance. Finally, a low-velocity servo turnable switched system is extensively simulated to demonstrate the effectiveness of the developed controller.  相似文献   

2.
This paper develops a novel way to control nonstrict-feedback nonlinear systems by using only one approximator, namely a neural network (NN) or a fuzzy logic system (FLS), in the first step of backstepping, such that the computational simplicity is ensured. The bounded property of basis functions solves the “algebraic loop” problem. The double-channel event-triggered control (ETC) is completed both in sensor-to-controller (SC) and controller-to-actuator (CA) channels, where the separate triggering conditions are fabricated. To solve the “jumps of virtual control laws (JVCL)” problem bedeviling the backstepping combined with ETC, this paper opens an avenue while guaranteeing the closed-loop stability with the aid of undetermined virtual control laws.  相似文献   

3.
Output feedback exponential stabilization of uncertain chained systems   总被引：4，自引：0，他引：4  
This paper deals with chained form systems with strongly nonlinear disturbances and drift terms. The objective is to design robust nonlinear output feedback laws such that the closed-loop systems are globally exponentially stable. The systematic strategy combines the input-state-scaling technique with the so-called backstepping procedure. A dynamic output feedback controller for general case of uncertain chained system is developed with a filter of observer gain. Furthermore, two special cases are considered which do not use the observer gain filter. In particular, a switching control strategy is employed to get around the smooth stabilization issue (difficulty) associated with nonholonomic systems when the initial state of system is known.  相似文献   

4.
A backstepping-based adaptive neural network decentralized stabilization approach is presented for the expanding construction of a class of nonlinear large scale interconnected systems in this paper. The expanding construction of large scale interconnected systems is to add some new subsystems into the original system during the operation of the original system. For stabilization of the expanding system, it is more realistic to keep the decentralized control laws of the original subsystems unchanged. And the decentralized control laws of the new subsystems must be designed to stabilize both itself and the resultant large scale system. In this paper, neural networks are used to approximate the unknown nonlinear functions in the new subsystems and the unknown nonlinear interconnection functions. The decentralized control laws and the parameter adaptive laws of the new subsystems are designed by using backstepping technique for the expanding construction of the large-scale interconnected system. Based on Lyapunov stability theory, the uniform and ultimate boundedness of all signals in the closed-loop system is proved. Two illustrative examples show the feasibility of the presented approach.  相似文献   

5.
《Journal of The Franklin Institute》2021,358(18):10029-10051
This paper is concerned with the problem of generating stable limit cycles for a class of nonlinear sandwich systems with the sandwiched dead-zone nonlinearity. In this study, the considered sandwich systems are restricted to the potential problems of non-symmetric input saturation nonlinearity and unknown parameters. In this regard, based on the set stabilization approach and the shape of the desired limit cycle, an adaptive state feedback controller is constructed by using the backstepping technique in such a way that forces the system's output to oscillate with the wanted amplitude and frequency. Besides, to estimate the value of unknown parameters, the adaptive laws are extracted and the problem of the explosion of complexity in the traditional backstepping approach is solved via an effective differentiator. The Lyapunov stability analysis proves that all signals of the closed-loop system keep bounded. Finally, the simulation results of a practical example are provided to demonstrate the effectiveness of the proposed method.  相似文献   

6.
Most extant control designs for uncertain pure-feedback systems are based on backstepping procedure or dynamic surface control, requiring repeated calculation or approximation of the derivatives of the virtual control action. The fuzzy logic systems or neural networks used to cope with unknown dynamics also inherently introduce excess computation burden and sluggish convergence. In view of these, this paper provides a novel backstepping approach by combining extended state observers with dynamic inversion controllers. With high gain properties both on the observers and controllers, the resulting closed-loop system presents relatively fast convergence. By using dynamic inversion backstepping, the explosion of complexity problem that restricts the applicability of backstepping-like control methods, which are representatively employed to the control of pure-feedback systems, is entirely surmounted without resorting to filtering. The theoretical analysis of stability shows the closed-loop system has adjustable tracking performance. Finally, the efficiency of the proposed method is illustrated by comparative simulations.  相似文献   

7.
This paper concentrates on proposing a novel finite-time tracking control algorithm for a kind of nonlinear systems with input quantization and unknown control directions. The nonlinear functions in the system are approximated by the means of strong approximation capability of the fuzzy logic systems. Firstly, the nonlinear system with unknown control directions is transformed into an equivalent system with known control gains by coordinate transformation. Secondly, the unknown system states are estimated by a designed fuzzy state observer, and the disturbance observer is constructed to track the external disturbances. The command filtering method is proposed to approach the problem of “explosion of complexity” existed in the conventional backstepping design process. In this system, the difficulties caused by unknown control directions are solved via the Nussbaum gain approach. Finally, based on the fuzzy state observer, the controller of the original system is obtained via using the transformed system by the backstepping method. The boundedness of all signals and the convergence of tracking and observer errors at the origin are ensured for the closed-loop system, and demonstrated by the simulation result in this paper.  相似文献   

8.
In this paper, the adaptive prescribed performance tracking control of nonlinear asymmetric input saturated systems in strict-feedback form is addressed under the consideration of model uncertainties and external disturbances. A radial basis function neural network (RBF-NN) is utilized to handle the model uncertainties. By prescribed performance functions, the transient performance of the system can be guaranteed. The continuous Gaussian error function is represented as an approximation of asymmetric saturation nonlinearity such that the backstepping technique can be leveraged in the control design. Based on the Lyapunov synthesis, residual function approximation inaccuracies and external disturbances are compensated by constructed adaptive control laws. As a consequence, all the signals in the closed-loop system are uniformly ultimately bounded and the tracking errors bounded by prescribed functions converge to a small neighbourhood of zero. The proposed method is applied to the autonomous underwater vehicles (AUVs) with extensive simulation results demonstrating the effectiveness of the proposed method.  相似文献   

9.
A control system of an ODE and a diffusion PDE is discussed in this paper. The novelty lies in that the system is coupled. The method of PDE backstepping as well as some special skills is resorted in stabilizing the coupled PDE–ODE control system, which is transformed into an exponentially stable PDE–ODE cascade with an invertible integral transformation. And a state feedback boundary controller is designed. Moreover, an exponentially convergent observer for anti-collocated setup is proposed, and the output feedback boundary control problem is solved. For both the state and output feedback boundary controllers, exponential stability analyses in the sense of the corresponding norms for the resulting closed-loop systems are given through rigid proofs.  相似文献   

10.
Limitations of the standard backstepping control technique are overcome in this paper by yielding global conditions for regional ones; specifically, flexible cascade arrangements that do not require the system to be put in a pure- or strict-feedback form to ensure controllability beforehand, handling of nonlinear MIMO blocks without invertible input distribution matrices, calculation of virtual and real control laws regardless of the non-affine-in-control nature of subsystems, and systematic numerical synthesis of Lyapunov-based control laws at each step of the cascade connection via linear matrix inequalities. All these benefits derive from exploiting exact convex rewriting of nonlinear terms, splitting available and non-available signals for control implementation, and applying the direct Lyapunov method to cast conditions as a convex optimization problem. Examples of academic and practical interest illustrate the advantages of the novel methodology over former approaches.  相似文献   

11.
This paper investigates the adaptive fuzzy control design problem of multi-input and multi-output (MIMO) non-strict feedback nonlinear systems. The considered control systems contain unknown control directions and dead zones. Fuzzy logic systems (FLSs) are utilized to approximate the unknown nonlinear functions, and the state observers are designed to estimate immeasurable states. By constructing a dead zone compensator and introducing a Nussbaum gain function into the backstepping technique, an adaptive fuzzy output feedback control method is developed. The proposed adaptive fuzzy controller is proved to guarantee the semi-globally uniformly ultimately bounded (SGUUB) of the closed-loop system, and can solve the control design problems of unmeasured states, unknown control directions and dead zones. The simulation results are given to demonstrate the effectiveness of the proposed control method.  相似文献   

12.
In this paper, a sensorless speed control for interior permanent magnet synchronous motors (IPMSM) is designed by combining a robust backstepping controller with integral actions and an adaptive interconnected observer. The IPMSM control design generally requires rotor position measurement. Then, to eliminate this sensor, an adaptive interconnected observer is designed to estimate the rotor position and the speed. Moreover, a robust nonlinear control based on the backstepping algorithm is designed where an integral action is introduced in order to improve the robust properties of the controller. The stability of the closed-loop system with the observer–controller scheme is analyzed and sufficient conditions are given to prove the practical stability. Simulation results are shown to illustrate the performance of the proposed scheme under parametric uncertainties and low speed. Furthermore, the proposed integral backstepping control is compared with the classical backstepping controller.  相似文献   

13.
In this paper, a L’ Hopital’s rule-based adaptive dynamic surface control (L-ADSC) scheme is developed for a class of strict-feedback systems with unknown parameters using backstepping technique. The L-ADSC-derived backstepping technique is deployed to remove differentiation of complex virtual controller, thereby efficiently avoiding ”exlosion of complexity”. The L’ Hopital’s Rule is resorted to tackle singularity problem within controller synthesis. As a consequence, the proposed L-ADSC scheme guarantees that all signals of the closed-loop control system are semi-globally uniformly ultimately bounded. Simulation results show remarkable effectiveness.  相似文献   

14.
In this paper, a security consistent tracking control scheme with event-triggered strategy and sensor attacks is developed for a class of nonlinear multi-agent systems. For the sensor attacks on the system, a security measurement preselector and a state observer are introduced to combat the impact of the attacks and achieve secure state estimation. In addition, command filtering technology is introduced to overcome the “complexity explosion” caused by the use of the backstepping approach. Subsequently, a new dynamic event-triggered strategy is proposed, in which the triggering conditions are no longer constants but can be adjusted in real time according to the adaptive variables, so that the designed event-triggered mechanism has stronger online update ability. The measurement states are only transmitted through the network based on event-triggered conditions. The proposed adaptive backstepping algorithm not only ensures the security of the system under sensor attacks but also saves network resources and ensures the consistent tracking performance of multi-agent systems. The boundedness of all closed-loop signals is proved by Lyapunov stability analysis. Simulation examples show the effectiveness of the control scheme.  相似文献   

15.
The current paper addresses the fuzzy adaptive tracking control via output feedback for single-input single-output (SISO) nonlinear systems in strict-feedback form. Under the situation of system states being unavailable, the system output is used to set up the state observer to estimate the real system states. Furthermore, the estimation states are employed to design controller. During the control design process, fuzzy logic systems (FLSs) are used to model the unknown nonlinearities. A novel observer-based finite-time tracking control scheme is proposed via fuzzy adaptive backstepping and barrier Lyapunov function approach. The suggested fuzzy adaptive output feedback controller can force the output tracking error to meet the pre-specified accuracy in a fixed time. Meanwhile, all the closed-loop variables are bounded. Compared to some existing finite-time output feedback control schemes, the developed control strategy guarantees that the settling time and the error accuracy are independent of the uncertainties and can be specified by the designer. At last, the effectiveness and feasibility of the proposed control scheme are demonstrated by two simulation examples.  相似文献   

16.
This paper develops a robust adaptive neural network (NN) tracking control scheme for a class of strict-feedback nonlinear systems with unknown nonlinearities and unknown external disturbances under input saturation. The radial basis function NNs with minimal learning parameter (MLP) are employed to online approximate the uncertain system dynamics. The adaptive laws are designed to online update the upper bound of the norm of ideal NN weight vectors, and the sum of the bounds of NN approximation errors and external disturbances, respectively. An auxiliary dynamic system is constructed to generate the augmented error signals which are used to modify the adaptive laws for preventing the destructive action due to the input saturation. Moreover, the command filtering backstepping control method is utilized to overcome the shortcoming of dynamic surface control method, the tracking-differentiator-based control method, etc. Our proposed scheme is qualified for simultaneously dealing with the input saturation effect, the heavy computational burden and the “explosion of complexity” problems. Theoretical analysis illuminates that our scheme ensures the boundedness of all signals in the closed-loop systems. Simulation results on two examples verify the effectiveness of our developed control scheme.  相似文献   

17.
In this paper, we propose a feedback-based control approach to execute the time optimal motion trajectories for a differential drive robot. These trajectories are composed of straight lines and rotations in place. We show that the evolution of the position of a single landmark over time, in a local reference frame, makes it possible to track a prescribed time-optimal robot’s trajectory, based on feedback of the landmark’s position. We also show that the closed-loop system is an exponentially stable one with a nonvanishing perturbation, and that globally uniformly ultimately boundedness of the tracking errors can be achieved. The two main results of this work are: 1) Our approach leverages visual servo control type of methods with tools from optimal control for executing time-optimal trajectories in the state space based on feedback information. 2) The approach is able to work with the minimum number of landmarks–only one–this represents a necessary and sufficientcondition for landmark-based navigation. Experiments in a physical robot, a nonholonomic differential drive system equipped with an omnidirectional laser sensor, are shown, which validate the proposed theoretical modelling.  相似文献   

18.
This paper concerns an adaptive fuzzy tracking control problem for a class of switched uncertain nonlinear systems in strict-feedback form via the modified backstepping technique. The unknown nonlinear functions are approximated by the generalized fuzzy hyperbolic model (GFHM). It is shown that if the designed parameters in the controller and adaptive laws are appropriately selected, then all closed-loop signals are bounded and the stability of the system can be kept under average dwell time methods. In the end, simulation studies are presented to illustrate the effectiveness of the proposed method.  相似文献   

19.
In this paper, we develop two new model reference adaptive control (MRAC) schemes for a class of nonlinear dynamic systems that is robust with respect to an uncertain state (output) dependent nonlinear perturbations and/or external disturbances with unknown bounds. The design is based on a controller parametrization with an adaptive integral action. Two types of adaptive controllers are considered—the state feedback controller with a plant parameter identifier, and the output feedback controller with a linear observer.  相似文献   

20.
In this paper, the problem of adaptive fuzzy fault-tolerant control is investigated for a class of switched uncertain pure-feedback nonlinear systems under arbitrary switching. The considered actuator failures are modeled as both lock-in-place and loss of effectiveness. By utilizing mean value theorem, the considered pure-feedback systems are transformed into a class of switched nonlinear strict-feedback systems. Under the framework of backstepping design technique and common Lyapunov function (CLF), an adaptive fuzzy fault-tolerant control (FTC) method with predefined performance bounds is developed. It is proved that under the proposed controller, all the signals of the close-loop systems are bounded and the state tracking error for each step remains within the prescribed performance bound (PPB) regardless of actuator faults and the system switchings. In addition, the tracking errors and magnitudes of control inputs can be reduced by adjusting the PPB parameters of errors in the first and last steps. The simulation results are provided to show the effectiveness of the proposed control scheme.  相似文献   

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