首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 432 毫秒
1.
In this paper, a dynamic extremum seeking scheme is designed for a class of three-player attack-defense problems with unknown gradient, where an attacker intends to strike a non-maneuverable headquarters, while a defender attempts to prevent this attack. Firstly, a kinematic equation is utilized to model the defender’s patrolling algorithm based on the law of gravitation. Then, a gradient estimation algorithm is employed to obtain derivatives of performance functions. In virtue of the Lyapunov function method, sufficient conditions are derived to guarantee the asymptotical stability of the closed-loop dynamic extremum seeking system. Finally, a group of simulations on wheeled mobile robot systems are exploited to illustrate the effectiveness of the proposed extremum seeking scheme.  相似文献   

2.
In this paper, a solution for improvement of transient performance in adaptive control of nonlinear systems is proposed. An optimal adaptive controller based on a reset mechanism and a prescribed performance bound is devised. The suggested controller has the structure of adaptive backstepping controller in which the estimated parameters are reset to an optimal value. The designed controller ensures both the transient bound and the asymptotical convergence of the states. It is shown that the tracking error satisfies the prescribed performance bound all the time, besides the speed of the convergence rate is increased by resetting the estimated parameters. The results have been proved through both the analytical and simulation studies. The proposed method is applied to an Augmented Quarter Car Model as a case study. Simulation results verify the established theoretical consequences that the prescribed performance bound based optimal adaptive reset controller can enhance the transient performance of the adaptive controller.  相似文献   

3.
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   

4.
This paper studies the problem of finite-time formation tracking control for networked nonaffine nonlinear systems with unmeasured dynamics and unknown uncertainties/disturbances under directed topology. A unified distributed control framework is proposed by integrating adaptive backstepping control, dynamic gain control and dynamic surface control based on finite-time theory and consensus theory. Auxiliary dynamics are designed to construct control gains with non-Lipschitz dynamics so as to guarantee finite-time convergence of formation errors. Adaptive control is used to compensate for uncertain control efforts of the transformed systems derived from original nonaffine systems. It is shown that formation tracking is achieved during a finite-time period via the proposed controller, where fractional power terms are only associated with auxiliary dynamics instead of interacted information among the networked nonlinear systems in comparison with most existing finite-time cooperative controllers. Moreover, the continuity of the proposed controller is guaranteed by setting the exponents of fractional powers to an appropriate interval. It is also shown that the improved dynamic surface control method could guarantee finite-time convergence of formation errors, which could not be accomplished by conventional dynamic surface control. Finally, simulation results show the effectiveness of the proposed control scheme.  相似文献   

5.
开关磁阻电动机的非线性模型预测控制   总被引：3，自引：0，他引：3  
葛宝明  蒋静坪 《科技通报》1999,15(6):418-422,427
将非线性预测控制应用于ＳＲＭ传动系统,建立了非线性参数预测模型,并在此基础上优化、校正,设计了ＳＲＭ的非线性速度预测控制器。该控制器具有实时预测、实时优化、实时校正的特点,很好地补偿了ＳＲＭ的非线性特性。与传统ＰＩ控制器相比,非线性模型预测控制器能提供更好的动态、静态特性,转矩脉动大为减小。（仿真结果表明,该控制策略不但正确、有效,而且使ＳＲＭ传动系统性能得到改善。  相似文献   

6.
This paper uses repetitive process stability theory to design robust iterative learning control law for linear discrete systems with multiple time-delays and polytopic uncertainty. Both dynamic and static forms of the control law are considered and used when designing robust iterative learning control schemes. Also, based on the generalized Kalman-Yakubovich-Popov Lemma, the proposed design procedures a required frequency attenuation over a finite frequency range and the monotonic trial-to-trial error convergence. Moreover, linear matrix inequality techniques are applied to formulate the convergence conditions and to obtain formulas for the control law designs. Finally, an illustrative numerical simulation example is given and concludes the paper.  相似文献   

7.
In this paper, a novel event-triggered adaptive fault-tolerant control scheme is proposed for a class of nonlinear systems with unknown actuator faults. Multiplicative faults and additive faults are taken into account simultaneously, both of which may vary with time. Different from existing results, our controller fuses static reliability information and dynamic online information, which is helpful to enhance the fault-tolerant capability. With the aid of an event-triggering mechanism, an actuator switching strategy and a bound estimation approach, the communication burden is significantly reduced and the impacts of the actuator faults as well as the network-induced error are effectively compensated for. Moreover, by employing the prescribed performance control technique, the system tracking error can converge to a predefined arbitrarily small residual set with prescribed convergence rate and maximum overshoot, which implies that the proposed scheme is able to ensure rapid and accurate tracking. Simulation results are presented to illustrate the effectiveness of the proposed scheme.  相似文献   

8.
This paper develops a new dual ML-ADHDP method to solve the optimal consensus problem (OCP) of a class of heterogeneous discrete-time nonlinear multi-agent systems (MASs) with unknown dynamics and time delay. A hierarchical and distributed control strategy is used to transform the original problem into nonlinear model reference adaptive control (MRAC) problems and an OCP of virtual linear MASs. For the nonlinear MRAC problems, a new multi-layer action-dependent heuristic dynamic programming (ML-ADHDP) method is developed to overcome the unknown dynamics and neural network estimation errors, which has higher control accuracy. In order to solve the OCP of virtual linear MASs and improve the convergence speed, a new multi-layer performance index is proposed. Then the ML-ADHDP method is used to solve the coupled Hamiltonian–Jacobi–Bellman equation and obtain the optimal virtual control. Theoretical analysis proves that the original MASs can achieve Nash equilibrium, and simulation results show that the developed dual ML-ADHDP method ensures better convergence speed and higher control accuracy of original MASs.  相似文献   

9.
This paper investigates the optimal tracking control problem (OTCP) for nonlinear stochastic systems with input constraints under the dynamic event-triggered mechanism (DETM). Firstly, the OTCP is converted into the stabilizing optimization control problem by constructing a novel stochastic augmented system. The discounted performance index with nonquadratic utility function is formulated such that the input constraint can be encoded into the optimization problem. Then the adaptive dynamic programming (ADP) method of the critic-only architecture is employed to approximate the solutions of the OTCP. Unlike the conventional ADP methods based on time-driven mechanism or static event-triggered mechanism (SETM), the proposed adaptive control scheme integrates the DETM to further lighten the computing and communication loads. Furthermore, the uniform ultimately boundedness (UUB) of the critic weights and the tracking error are analysed with the Lyapunov theory. Finally, the simulation results are provided to validate the effectiveness of the proposed approach.  相似文献   

10.
邱晓华  陈偕雄 《科技通报》2007,23(6):867-872
讨论了单输入单输出ARMAX系统在非高斯噪声环境下的参数估计问题。提出了一种基于M估计理论的系统参数动态递推辨识算法,利用函数逼近原理以及矩阵等价变换知识,给出了算法的详细推导过程,分析了M估计用于系统建模的原理,给出了适合在线计算的参数估计递推算法。最后进行了数值仿真,结果表明本文提出的算法具有较强的抗噪能力和良好的收敛性。  相似文献   

11.
为了提高直流调速系统的动静态性能指标,通常采用闭环控制系统（包括单闭环系统和多闭环系统）。对调速指标要求不高的场合,采用单闭环系统,而对调速指标较高的则采用多闭环系统。按反馈的方式不同可分为转速反馈,电流反馈,电压反馈等。在单闭环系统中,转速单闭环使用较多。  相似文献   

12.
《Journal of The Franklin Institute》2023,360(14):10564-10581
In this work, we investigate consensus issues of discrete-time (DT) multi-agent systems (MASs) with completely unknown dynamic by using reinforcement learning (RL) technique. Different from policy iteration (PI) based algorithms that require admissible initial control policies, this work proposes a value iteration (VI) based model-free algorithm for consensus of DTMASs with optimal performance and no requirement of admissible initial control policy. Firstly, in order to utilize RL method, the consensus problem is modeled as an optimal control problem of tracking error system for each agent. Then, we introduce a VI algorithm for consensus of DTMASs and give a novel convergence analysis for this algorithm, which does not require admissible initial control input. To implement the proposed VI algorithm to achieve consensus of DTMASs without information of dynamics, we construct actor-critic networks to online estimate the value functions and optimal control inputs in real time. At last, we give some simulation results to show the validity of the proposed algorithm.  相似文献   

13.
In this paper, the appointed-time prescribed performance and finite-time tracking control problem is investigated for quadrotor unmanned aerial vehicle (QUAV) in the presence of time-varying load, unknown external disturbances and unknown system parameters. For the position loop, a novel appointed-time prescribed performance control (ATPPC) strategy is proposed based on adaptive dynamic surface control (DSC) frameworks and a new prescribed performance function to achieve the appointed-time convergence and prescribed transient and steady-state performance. For the attitude loop, a new finite-time control strategy is proposed based on a new designed sliding mode control technique to track the desired attitude in finite time. Some assumptions of knowing system parameters are canceled. Finally, the stability of the closed-loop system is proved via Lyapunov Theory. Simulations are performed to show the effectiveness and superiority of the proposed control scheme.  相似文献   

14.
This paper investigates the problem of asymptotic tracking control of nonlinear robotic systems with prescribed performance. The control strategy is developed based on a modified prescribed performance function (PPF) to guarantee the transient behavior, while the requirements on the accurate initial tracking error in the classical PPF can be remedied. The fuzzy logic system (FLS) is used to approximate the unknown dynamics. In the existing PPF based adaptive control schemes with FLSs, the tracking error does not achieve asymptotic convergence. To address this issue, a robust integral of the sign of the error (RISE) term is incorporated into the control design to reject the FLS approximation errors and external disturbances, such that the asymptotic convergence is achieved. Finally, numerical simulation and experimental results validate the effectiveness of the proposed control scheme.  相似文献   

15.
In order to improve the anti-disturbance performance of a bearingless induction motor (BIM) control system, a fractional-order sliding mode control (FOSMC) strategy based on improved load torque observer is proposed on the basis of the sliding mode speed regulation system. Using the information memory and genetic characteristics of the fractional calculus operator, the fractional integral term of the speed error is introduced in the design of the traditional sliding surface, which reduces the influence of disturbance on the speed regulation system. The fractional-order sliding mode control law is derived based on the BIM mathematical model, and the stability of the control law is proved by Lyapunov theorem. An improved observer is constructed based on the BIM state equations, and the real-time observed load torque is introduced into the fractional-order sliding mode controller. To improve the observer's convergence speed, the proportional integral form is used to replace the integral form in the traditional reduced order load observer. And the state error feedback coefficients of the improved load observer are calculated. Both simulation and experimental results verified the effectiveness of the proposed control strategy.  相似文献   

16.
《Journal of The Franklin Institute》2022,359(18):10355-10391
In this paper, an adaptive neural finite-time tracking control is studied for a category of stochastic nonlinearly parameterized systems with multiple unknown control directions, time-varying input delay, and time-varying state delay. To this end, a novel criterion of semi-globally finite-time stability in probability (SGFSP) is proposed, in the sense of Lyapunov, for stochastic nonlinear systems with multiple unknown control directions. Secondly, a novel auxiliary system with finite-time convergence is presented to cope with the time-varying input delay, the appropriate Lyapunov Krasovskii functionals are utilized to compensate for the time-varying state delay, Nussbaum functions are exploited to identify multiple unknown control directions, and the neural networks (NNs) are applied to approximate the unknown functions of nonlinear parameters. Thirdly, the fraction dynamic surface control (FDSC) technique is embedded in the process of designing the controller, which not only the “explosion of complexity” problems are successfully avoided in traditional backstepping methods but also the command filter convergence can be obtained within a finite time to lead greatly improved for the response speed of command filter. Meanwhile, the error compensation mechanism is established to eliminate the errors of the command filter. Then, based on the proposed novel criterion, all closed-loop signals of the considered systems are SGPFS under the designed controller, and the tracking error can drive to a small neighborhood of the origin in a finite time. In the end, three simulation examples are applied to demonstrate the validity of the control method.  相似文献   

17.
The introduction of advanced control algorithms may improve considerably the efficiency of wind turbine systems. This work proposes a high order sliding mode (HOSM) control scheme based on the super twisting algorithm for regulating the wind turbine speed in order to obtain the maximum power from the wind. A robust aerodynamic torque observer, also based on the super twisting algorithm, is included in the control scheme in order to avoid the use of wind speed sensors. The presented robust control scheme ensures good performance under system uncertainties avoiding the chattering problem, which may appear in traditional sliding mode control schemes. The stability analysis of the proposed HOSM observer is provided by means of the Lyapunov stability theory. Experimental results show that the proposed control scheme, based on HOSM controller and observer, provides good performance and that this scheme is robust with respect to system uncertainties and external disturbances.  相似文献   

18.
This paper presents a new Takagi-Sugeno-Kang fuzzy Echo State Neural Network (TSKFESN) structure to design a direct adaptive control for uncertain SISO nonlinear systems. The proposed TSKFESN structure is based on the echo state neural network framework containing multiple sub-reservoirs. Each sub-reservoir is weighted with a TSK fuzzy rule. The adaptive law of the TSKFESN-based direct adaptive controller is derived by using a fractional-order sliding mode learning algorithm. Moreover, the Lyapunov stability criterion is employed to verify the convergence of the fractional-order adaptive law of the controller parameters. The evaluation of the proposed direct adaptive control scheme is verified using two case studies, the regulation problem of a torsional pendulum and the speed control of a direct current (DC) machine as a real-time application. The simulation and the experimental results show the effectiveness of the proposed control scheme.  相似文献   

19.
The existing studies on prescribed-time control cannot directly deal with nonlinear functions which don’t satisfy Lipschitz growth conditions. No results are available for prescribed-time containment control of pure-feedback UNMASs with prescribed performance. Therefore, completely unknown nonlinear function, prescribed-time tracking of system states and prescribed performance of containment errors are simultaneously considered in this paper. Fuzzy logic systems are utilized to approximate completely unknown nonlinear function. Prescribed-performance function is introduced and further incorporated into a novel speed function. Combining the proposed speed function and barrier Lyapunov function, this article presents a novel adaptive fuzzy prescribed-time containment control method which can guarantee, under prescribed performance, all followers converge to a convex formed by dynamic leaders in a prescribed time. Moreover, all tracking errors converge to predefined regions in a prescribed time. The effectiveness of the proposed prescribed-time containment control method are confirmed by strict proof and simulation.  相似文献   

20.
信息技术投资绩效应该是一个动态变化的过程,而且受到国家特征的影响,但当前的研究往往忽视了国家特征对信息技术投资绩效的影响。本文在传统局部调整模型的基础上,假设调整速度是动态变动的,且是国家特征的线性函数,提出了一种基于动态调整速度的局部调整模型。该模型可以分析统计期内信息技术投资绩效的动态变化过程,及其与调整速度的关系。结果表明,信息技术投资对中国经济增长的影响并不显著,信息技术作为生产要素进入生产过程后,导致经济绩效的下降,中国存在信息技术的“生产率悖论”现象。  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号