共查询到20条相似文献,搜索用时 15 毫秒
1.
In this paper, an adaptive predictive control algorithm is applied to control a class of SISO continuous stirred tank reactor (CSTR) system in discrete time. The main contribution of the paper is that the considered systems belong to pure-feedback form where the unknown dead-zone is considered in the in-fan, and dead-zone is nonsymmetric, and it is first to control this class of systems. Radial basis function neural networks are used to approximate the unknown functions, and the mean value theorem is exploited in the design. Based on the Lyapunov analysis method, it is proven that all the signals of the resulting closed-loop system are guaranteed to be semi-global uniformly ultimately bounded, and the tracking error can be reduced to a small compact set. A simulation example for CSTR systems is studied to verify the effectiveness of the proposed approach. 相似文献
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A direct adaptive control framework for linear uncertain systems for using communication channels is developed. Specifically, the control signals are to be quantized and sent over a communication channel to the actuator. The proposed framework is Lyapunov-based and guarantees partial asymptotic stability, that is, Lyapunov stability of the closed-loop system states and attraction with respect to the plant states. The quantizers are logarithmic and characterized by sector-bound conditions, with the conic sectors adjusted at each time instant by the adaptive controller, in conjunction with the system response. Furthermore, we extend the scheme to the case where the logarithmic quantizer has a deadzone around the origin so that only a finite number of quantization levels is required to achieve practical stability. Finally, a numerical example is provided to demonstrate the efficacy of the proposed approach. 相似文献
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非线性离散时间系统的自适应模糊补偿控制 总被引:1,自引:0,他引:1
针对一类非线性离散时间系统,提出一种自适应模糊逻辑补偿控制方案.控制律由跟踪控制律和逼近误差补偿控制律两部分组成,利用模糊逻辑系统对系统参数扰动和外界干扰进行自适应补偿,由模糊滑模控制律实现对模糊逻辑系统逼近误差的进一步补偿.所设计的控制器可保证闭环系统一致最终有界.将该控制器用于月球探测车动态转向系统中,仿真结果表明了该方法的有效性. 相似文献
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Xinkai Chen Author Vitae 《Automatica》2006,42(3):427-435
In this paper, robust adaptive sliding mode tracking control for discrete-time multi-input multi-output systems with unknown parameters and disturbance is considered. The robust tracking controller is comprised of adaptive control and sliding mode control design. Bounded motion of the system around the sliding surface and stability of the global system in the sense that all signals remain bounded are guaranteed. If the disturbance and the reference signal are slowly varying with respect to the sampling frequency, the proposed sliding mode controller can reject the disturbance and output tracking can be approximately achieved. Simulation results are presented to illustrate the proposed approach. 相似文献
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针对一类非线性离散系统, 利用Lyapunov方法和加权最小二乘估计设计了一种自适应控制器, 在不对非线性加增长条件约束的情况下, 得到了闭环系统的全局跟踪性能. 相似文献
6.
This study focuses on state-feedback and output-feedback neural learning control problems for discrete-time nonlinear systems in the pure-feedback form.First,an... 相似文献
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Adaptive control of discrete-time systems using multiple models 总被引:1,自引:0,他引:1
The adaptive control of a linear time-invariant discrete-time system using multiple models is considered in this paper. Both the deterministic (noise free) case and the stochastic case when random disturbances are present are discussed. Based on the prediction errors of a finite number of fixed and adaptive identification models, a procedure is outlined for switching between a finite number of controllers to improve performance. The principal contributions of the paper are the proof of global stability of the overall system and the convergence of the tracking error signal to zero in the deterministic case and the proof of convergence of the minimum variance control problem. Computer simulation results are included to complement the theoretical results 相似文献
10.
The problem of adaptive dual control of discrete-time distributed-parameter stochastic systems is examined. It is shown that there exists an important difference between feedback and closed-loop policies of control for this type of system as for the lumped parameter case. This difference is based on the adaptivity feature of the control. Namely, when the control policy affects both the state and its uncertainty (dual effect) it possesses the so-called feature of active adaptivity and can only be a characteristic of a closed-loop policy, whereas a feedback policy can only be passively adaptive. These results can be used to develop a control algorithm for non-linear problems for which the realization of optimal control laws involves control strategies with both learning and control features. 相似文献
11.
Adaptive policies for discrete-time stochastic control systems with unknown disturbance distribution
We introduce adaptive policies for discrete-time, infinite horizon, stochastic control systems x1+1 = F(x1, a1, ξ1, T =0, 1, …, with discounted reward criterion, where the disturbance process ξ1 is a sequence of i.i.d. random elements with unknown distribution. These policies are shown to be asymptotically optimal and for each of them we obtain (almost surely) uniform approximations of the optimal reward function. 相似文献
12.
In this paper, both full state and output feedback adaptive neural network (NN) controllers are presented for a class of strict-feedback discrete-time nonlinear systems. Firstly, Lyapunov-based full-state adaptive NN control is presented via backstepping, which avoids the possible controller singularity problem in adaptive nonlinear control and solves the noncausal problem in the discrete-time backstepping design procedure. After the strict-feedback form is transformed into a cascade form, another relatively simple Lyapunov-based direct output feedback control is developed. The closed-loop systems for both control schemes are proven to be semi-globally uniformly ultimately bounded. 相似文献
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This paper studies data-driven learning-based methods for the finite-horizon optimal control of linear time-varying discrete-time systems. First, a novel finite-horizon Policy Iteration (PI) method for linear time-varying discrete-time systems is presented. Its connections with existing infinite-horizon PI methods are discussed. Then, both data-driven off-policy PI and Value Iteration (VI) algorithms are derived to find approximate optimal controllers when the system dynamics is completely unknown. Under mild conditions, the proposed data-driven off-policy algorithms converge to the optimal solution. Finally, the effectiveness and feasibility of the developed methods are validated by a practical example of spacecraft attitude control. 相似文献
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In this paper, an adaptive critic neural network controller is designed for a class of discrete-time chaotic system. The critic neural network is used to approximate the long-term function. In contrast with the existing results for discrete-time chaotic systems, in this paper, a near optimal control input can be generated when the long-term function is minimized. It is proven that the tracking error, the adaptation laws and the control input are uniformly bounded. A simulation example is employed to illustrate the effectiveness of the proposed algorithm. 相似文献
16.
Califano C. Monaco S. Normand-Cyrot D. 《Automatic Control, IEEE Transactions on》1998,43(11):1654-1658
Necessary and sufficient conditions under which the discrete-time normal form exists are set both in geometric and in algebraic frameworks, leading to equivalent conditions. The results are therefore extended to generic nonlinear nonaffine continuous-time systems 相似文献
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Han-Fu Chen Qian Wang 《Automatic Control, IEEE Transactions on》2001,46(11):1836-1840
A direct adaptive regulator for nonlinear nonparametric systems with measurement corrupted by noise is proposed. Under reasonable conditions the state of the closed-loop system is adaptively regulated so that it converges to zero as time tends to infinity. An illustrative example, being an affine nonlinear system, with all imposed conditions satisfied is given. The method of proof is based on stochastic approximation techniques 相似文献
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The adaptive control problem is addressed in the paper for a class of discrete-time affine nonlinear input/output stochastic models with linear unknown parameters. The controller is a certainty equivalence weighted one-step-ahead control and is constructed by using the weighted-least-squares and random regularization methods. Global stability of the closed-loop systems is established, which shows that arbitrarily large growth rate is allowed for the multiplicative nonlinear part of the systems. 相似文献
19.
T.-H. Kim 《International journal of control》2013,86(1):62-73
This paper proposes a discrete-time model predictive control (MPC) scheme combined with an adaptive mechanism. To this end, first, an adaptive parameter estimation algorithm suitable for MPC is proposed, which uses the available input and output signals to estimate the unknown system parameters. It enables the prediction of a monotonically decreasing worst-case estimation error bound over the prediction horizon of MPC. These distinctive features allow for future model improvement to be explicitly considered in MPC. Thus, a less conservative adaptive-type MPC controller can be developed based on the proposed estimation method. Second, we show how the discrete-time adaptive-type state-feedback MPC controller is constructed by combining the on-line parameter estimation scheme with a modified robust MPC method based on the comparison model. The developed MPC controller guarantees feasibility and stability of the closed-loop system theoretically in the presence of input and state constraints. A numerical example is given to demonstrate its effectiveness. 相似文献
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This note deals with quadratic observability normal form for nonlinear discrete-time single-input-single-output (SISO) system. First of all, the main concept of quadratic equivalence with respect to the observability property, is introduced for discrete-time systems. Subsequently, normal form structure for discrete time system is developed for system with unobservable linear approximation in one direction. Finally, the effect of the so-called resonant terms on the observer design and synchronization of chaotic systems is pointed out in an illustrative example. 相似文献