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1.
This paper studies the issue of finite-time performance guaranteed event-triggered (ET) adaptive neural tracking control for strict-feedback nonlinear systems with unknown control direction. A novel finite-time performance function is first constructed to describe the prescribed tracking performance, and then a new lemma is given to show the differentiability and boundedness of the performance function, which is important for the verification of the closed-loop system stability. Furthermore, with the help of the error transformation technique, the origin constrained tracking error is transformed into an equivalent unconstrained one. By utilizing the first-order sliding mode differentiator, the issue of “explosion of complexity” caused by the backstepping design is adequately addressed. Subsequently, an ingenious adaptive updated law is given to co-design the controller and the ET mechanism by the combination of the Nussbaum-type function, thus effectively handling the influences of the measurement error resulted from the ET mechanism and the challenge of the controller design caused by the unknown control direction. The presented event-triggered control scheme can not only guarantee the prescribed tracking performance, but also alleviate the communication burden simultaneously. Finally, numerical and practical examples are provided to demonstrate the validity of the proposed control strategy.  相似文献   

2.
This paper presents explicit and implicit discrete-time realizations for the robust exact filtering differentiator, aiming to facilitate an adequate posterior implementation structure in digital devices. This paper firstly presents an analysis of an explicit discrete-time realization of the filtering differentiator based on linear systems’ exact discretization with a zero-order holder. For this case, however, high-order terms in the filter dynamics may cause instability of the estimation error for signals with unbounded derivatives. Hence, two other new discrete-time realizations of the filtering differentiator are derived by removing some high-order terms in the filter dynamics. The first one is an explicit discrete-time realization, while the second one is implicit. After a finite time, both preserve the accuracy of the continuous-time robust exact filtering differentiator in the presence of measurement noise. For each proposed discrete-time scheme, a stability analysis based on homogeneity is provided. Finally, the simulation results include comparisons between the proposed implicit and explicit discrete-time realizations with other existing schemes. These numerical studies highlight that the implicit scheme supersedes the explicit one, consistent with the implicit and explicit realizations of other continuous-time algorithms.  相似文献   

3.
《Journal of The Franklin Institute》2019,356(17):10260-10276
This paper is concerned with the problem of distributed event-triggered controller design for networked control systems (NCSs) with stochastic cyber-attacks. A decentralized event-triggered scheme is introduced to save the energy consumption and alleviate the transmission load of the network. Each sensor can make its own decision to determine whether the sampled data is delivered to the network or not. By taking two kinds of random cyber-attacks into consideration, a novel mathematical model is constructed for distributed event-triggered NCSs. Sufficient conditions which can guarantee the stability of the control system are obtained by applying Lyapunov stability theory, and the design method of the controller gain is presented in an exact expression. Finally, an example is given to demonstrate the effectiveness of the proposed method.  相似文献   

4.
An Antilock Braking System (ABS) is characterized by nonlinear dynamics, which render more difficult the design of a controller for high performance. The problem is even harder due to the uncertainties on the parameters appearing in its dynamics. In this paper, an ABS laboratory setup is considered, which mimics a quarter car model. A super–twisting controller is proposed to overcome the problem due to parameter uncertainties. This controller is designed in order to impose a reference value of the tire slip. Two cases are considered: in the first, nominal ABS parameters are used in the controller, whereas in the second the controller embeds an estimator of the tire–road friction coefficient, which is one of most critical parameters. The friction coefficient is estimated in finite–time by means of a high–order sliding mode differentiator. The original contributions of the paper are the real–time implementation of the super–twisting controller for the laboratory setup under study, and the use of a super–twisting estimator to provide a finite–time estimation of the friction coefficient between the tire and the road, along with a comparison with classical PI–like and super–twisting controllers, available in the literature. The ABS laboratory setup allows checking experimentally the performance of the proposed nonlinear dynamic controller, showing a considerable increase of the efficiency of the control system.  相似文献   

5.
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   

6.
Gas flow has fractional order dynamics; therefore, it is reasonable to assume that the pneumatic systems with a proportional valve to regulate gas flow have fractional order dynamics as well. There is a hypothesis that the fractional order control has better control performance for this inherent fractional order system, although the model used for fractional controller design is integer order. To test this hypothesis, a fractional order sliding mode controller is proposed to control the pneumatic position servo system, which is based on the exponential reaching law. In this method, the fractional order derivative is introduced into the sliding mode surface. The stability of the controller is proven using Lyapunov theorem. Since the pressure sensor is not required, the control system configuration is simple and inexpensive. The experimental results presented indicate the proposed method has better control performance than the fractional order proportional integral derivative (FPID) controller and some conventional integral order control methods. Points to be noticed here are that the fractional order sliding mode control is superior to the integral order sliding mode counterpart, and the FPID is superior to the corresponding integral order PID, both with optimal parameters. Among all the methods compared, the proposed method achieves the highest tracking accuracy. Moreover, the proposed controller has less chattering in the manipulated variable, the energy consumption of the controller is therefore substantially reduced.  相似文献   

7.
In this paper, a fixed-time dual closed-loop attitude control method is investigated for a quadrotor unmanned aerial vehicle. Firstly, a fixed-time adaptive fast super-twisting disturbance observer is presented for estimating the unknown external disturbance. A modified adaptive law is employed based on an equivalent control method to obtain proper observer gains. Secondly, a fixed-time controller is designed by using a universal barrier Lyapunov function to satisfy asymmetric tracking error constraints. Then, a tracking differentiator is utilised to arrange the transition process. Finally, the implementation of the developed method in a quadrotor unmanned aerial vehicle is performed. Through stability analysis and simulation results, the effectiveness and superiority of the proposed fixed-time control method are validated.  相似文献   

8.
In this paper a sliding mode position control for high-performance real-time applications of induction motors is developed. The design also incorporates a sliding mode rotor flux estimator in order to avoid the flux sensors. The proposed control scheme presents a low computational cost and therefore can be implemented easily in a real-time applications using a low cost Digital Signal Processor (DSP). The stability analysis of the observer and the controller, under parameter uncertainties and load torque disturbances, is provided using the Lyapunov stability theory. Finally simulated and experimental results show that the proposed controller with the proposed observer provides a good trajectory tracking and that this scheme is robust with respect to plant parameter variations and external load disturbances.  相似文献   

9.
To achieve accurate position control of electro-hydraulic asymmetric cylinder system with only available displacement signal, an output feedback controller is proposed in this paper. The dynamic model of the system is expressed as a Brunovsky form, which helps to estimate the system states and simplify the controller structure. Then Levant differentiator is introduced to estimate the position, velocity and acceleration of the asymmetric cylinder system based on the output signal, which can reduce the impact of measurement noise compared to the means of calculating the time derivative of the displacement signal directly. Besides, a high gain disturbance observer is designed to reject the lumped disturbance rejection of the system including parameter uncertainty, modelling error and external disturbance. Moreover, a sliding mode surface is introduced to the controller design and a robust item with continuous function is applied to compensate for estimation errors. According to Lyapunov theory, the developed output controller is pledged to be stable that can realize disturbance rejection control as well as backstepping-free control. Furthermore, a large-size asymmetric cylinder experimental rig is set up to simulate practical applications environment. Comparative experimental results reveal the validity and potential practical meaning of the developed control approach.  相似文献   

10.
Stability and energy consumption have always been important issues in electric vehicle research. Excessive slip energy not only aggravates tire wear, but also consumes energy of electric vehicle. In order to ensure the lateral stability and to reduce the slip energy dissipation of the distributed drive electric vehicle (DDEV) equipped with Mechanical Elastic Wheel (MEW), an integrated framework considering both tire slip energy dissipation and lateral stability control is proposed. The SESC (Slip Energy and Stability Control) is a hierarchical control framework for DDEV with MEW. A PID speed tracking controller and an (Integral Terminal Slide Mode) ITSM controller are designed at the upper-level controller. The ITSM controller can improve the lateral stability of the vehicle by obtaining the desired yaw moment. Speed tracking controller can stabilize the speed of the vehicle and obtain the desired longitudinal force. At the lower-level controller, the brush model of the MEW is proposed to express tire slip energy. In order to reduce the error of the vehicle dynamics and the slip energy dissipation, a mixed objective function including a holistic corner controller (HCC) and a minimum tire slip energy characterization is proposed. The proposed control framework is verified by Carsim and Matlab/Simulink under emergency simulation conditions. The simulation results show that the SESC based method can improve the lateral stability of DDEV with MEW effectively, and has better performance compared with fuzzyPID+AD based method. Meanwhile, the SESC achieves less slip energy than conventional torque distribution method.  相似文献   

11.
In order to improve the response speed and control precision of the braking system with parameters uncertainty and nonlinear friction, a braking-by-wire system based on the electromagnetic direct-drive valve and a novel cascade control algorithm was proposed in this paper. An electromagnetic linear actuator directly drives the valve spool and rapidly adjusts the pressure of braking wheel cylinders. A dynamic model of electromagnetic direct-drive valve considering improved LuGre dynamic friction is established. A novel cascade control algorithm with an outside loop pressure fuzzy controller and an inside loop electromagnetic direct-drive valve position controller was proposed. An adaptive integral robust inside loop controller is designed by combining friction compensation adaptive control law, linear feedback, and integral robust control. The uncertainty parameters and the friction state are estimated online. The stability of the cascade controller is proved by the Lyapunov method. Then a multi-objective opitimizemization design method of control parameters is proposed, which combines a multi-objective game theory and a technique for order preference by similarity to ideal solution (TOPSIS) based on entropy weight. The results show that the pressurization time of cascade control is less than 0.09 s under the 15 MPa step target signal. The control precision is improved effectively by the cascade controller under the ARTEMIS condition.  相似文献   

12.
This paper studies a finite-time adaptive fuzzy control approach for a continuous stirred tank reactor (CSTR) with percent conversion constraint and uncertainties. This system is seen as a class of non-affine systems, and the system is resolved by the mean value theorem. Integral barrier Lyapunov functions (iBLFs) are used to handle output constraint in the design process of the finite-time adaptive controller. In order to calculate the time derivative of the virtual controller, a finite-time convergent differentiator (FTCD) is proposed, which can avert the issue of “explosion of complexity” in the backstepping design. Based on the finite time stability theory, the proposed approach not only ensures the closed-loop stability, but also guarantees tracking performance in a finite time. Finally, the simulation results on CSTR are showed to reveal the availability of the developed control scheme.  相似文献   

13.
This paper deals with the problem of adaptive output feedback neural network controller design for a SISO non-affine nonlinear system. Since in practice all system states are not available in output measurement, an observer is designed to estimate these states. In comparison with the existing approaches, the current method does not require any information about the sign of control gain. In order to handle the unknown sign of the control direction, the Nussbaum-type function is utilized. In order to approximate the unknown nonlinear function, neural network is firstly exploited, and then to compensate the approximation error and external disturbance a robustifying term is employed. The proposed controller is designed based on strict-positive-real (SPR) Lyapunov stability theory to ensure the asymptotic stability of the closed-loop system. Finally, two simulation studies are presented to demonstrate the effectiveness of the developed scheme.  相似文献   

14.
A novel adaptive sliding-mode control system is proposed in order to control the speed of an induction motor drive. This design employs the so-called vector (or field oriented) control theory for the induction motor drives. The sliding-mode control is insensitive to uncertainties and presents an adaptive switching gain to relax the requirement for the bound of these uncertainties. The switching gain is adapted using a simple algorithm which does not imply a high computational load. Stability analysis based on Lyapunov theory is also performed in order to guarantee the closed loop stability. Finally, simulation results show not only that the proposed controller provides high-performance dynamic characteristics, but also that this scheme is robust with respect to plant parameter variations and external load disturbances.  相似文献   

15.
In this study, an adaptive fractional order sliding mode controller with a neural estimator is proposed for a class of systems with nonlinear disturbances. Compared with traditional sliding mode controller, the new proposed fractional order sliding mode controller contains a fractional order term in the sliding surface. The fractional order sliding surface is used in adaptive laws which are derived in the framework of Lyapunov stability theory. The bound of the disturbances is estimated by a radial basis function neural network to relax the requirement of disturbance bound. To investigate the effectiveness of the proposed adaptive neural fractional order sliding mode controller, the methodology is applied to a Z-axis Micro-Electro-Mechanical System (MEMS) gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed control system can improve tracking performance as well as parameter identification performance.  相似文献   

16.
A new robust fault-tolerant controller scheme integrating a main controller and a compensator for the self-repairing flight control system is discussed. The main controller is designed for high performance of the original faultless system. The compensating controller can be seen as a standalone loop added to the system to compensate the effects of fault guaranteeing the stability of the system. A design method is proposed using nonlinear dynamic inverse control as the main controller and nonlinear extended state observer-based compensator. System robustness is greatly improved by using the new configuration controller. The stability of the whole closed-loop system is analyzed. Feasibility and validity of the new controller is demonstrated with an aircraft simulation example.  相似文献   

17.
In the present study, a novel technique is suggested for the adaptive non-linear model predictive control based on the fuzzy approach in three stages. In the presented approach, in the first stage, the prediction and control horizons are obtained from a fuzzy system in each control step. Another fuzzy system is employed to determine the weight factors before the optimization stage of developing new controller. The proposed controller gives the parameters of the model predictive control (MPC) in each control step in order to improve the performance of nonlinear systems. The proposed control scheme is compared with the traditional MPC and Generic Model Control for controlling MED-TVC process. The performances of the three proposed controllers have been investigated in the absence and presence of disturbance in order to evaluate the stability and robustness of the proposed controllers. The results reveal that the novel adaptive controller based on fuzzy approach performs better than the two other controllers in set-point tracking and disturbance rejection with lower IAE criteria. In addition, the average computational time for the adaptive MPC exhibits a decline of 34% in comparison with the traditional MPC.  相似文献   

18.
This paper studies the robust stochastic stabilization problem for a class of fuzzy Markovian jump systems with time-varying delay and external disturbances via sliding mode control scheme. Based on the equivalent-input-disturbance (EID) approach, an online disturbance estimator is implemented to reject the unknown disturbance effect on the considered system. Specifically, to obtain exact EID estimation Luenberger fuzzy state observer and a low-pass filter incorporated to the closed-loop system. Moreover, novel fuzzy EID-based sliding mode control law is constructed to ensure the stability of the closed-loop system with satisfactory disturbance rejection performance. By employing Lyapunov stability theory and some integral inequalities, a new set of delay-dependent robust stability conditions is derived in terms of linear matrix inequalities (LMIs). The resulting LMI is used to find the gains of the state-feedback controller and the state observer a for the resulting closed-loop system. At last, numerical simulations based on the single-link arm robot model are provided to illustrate the proposed design technique.  相似文献   

19.
This paper investigates a robust H∞ controller design for discrete-time polynomial fuzzy systems based on the sum-of-squares (SOS) approach when model uncertainties and external disturbances are simultaneously considered. At the beginning of the controller design procedure, a general discrete-time polynomial fuzzy control system proposed in this paper is used to represent a nonlinear system containing model uncertainties and external disturbances. Subsequently, through use of a nonquadratic Lyapunov function and the H∞ performance index, the novel SOS-based robust H∞ stability conditions are derived to guarantee the stability of the entire control system. By solving those stability conditions, control gains of the robust H∞ polynomial fuzzy controller are obtained. Because the model uncertainties and external disturbances are considered simultaneously in the controller design procedure, the closed-loop control system achieves greater robustness and H∞ performance against model uncertainties and external disturbances. Moreover, the novel operating-domain-based robust H∞ stability conditions are derived by considering the operating domain constraint to relax the conservativeness of solving the stability conditions. Finally, simulation results demonstrated the availability and effectiveness of the proposed stability conditions, which are more general than those used in existing approaches.  相似文献   

20.
Auto-structuring fuzzy neural system for intelligent control   总被引：1，自引：0，他引：1  
An auto-structuring fuzzy neural network-based control system (ASFNS), which includes the auto-structuring fuzzy neural network (ASFNN) controller and the supervisory controller, is proposed in this paper. The ASFNN is used as the main controller to approximate the ideal controller and the supervisory controller is incorporated with the ASFNN for coping with the chattering phenomenon of the traditional sliding-mode control. In the ASFNS, an automatic structure learning mechanism is proposed for network structure optimization, where two criteria of node-adding and node-pruning are introduced. It enables the ASFNN to determine the nodes autonomously while ensures the control performance. In the ASFNS, all the parameters are evolved by the means of the Lyapunov theorem and back-propagation to ensure the system stability. Thus, an intelligent control approach for adaptive control is presented, where the structure and parameter can be evolved simultaneously. The proposed ASFNS features the following salient properties: (1) on-line and model-free control, (2) relax design in controller structure, (3) overall system stability. To investigate the capabilities, the ASFNS is applied to a kind of nonlinear system control. Through the simulation results the advantages of the proposed ASFNS can be validated.  相似文献   

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