线性离散系统中一种新的h -∞跟踪控制算法

IF 0.7 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Jordan Journal of Electrical Engineering Pub Date : 2022-01-01 DOI:10.5455/jjee.204-1654826074
S. Nakamori
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引用次数: 2

摘要

针对线性离散系统,提出了一种新的h∞二次跟踪控制算法。该算法是基于积分方程方法的线性连续系统中h -∞QTC算法的对应算法。本文的离散时间状态方程具有控制输入和外生输入。定理1通过求解两点边值问题(TPBVP)给出了h -∞线性QTC问题的控制输入和外生输入。在TPBVP的基础上,定理2给出了控制输入和外生输入的h -∞线性QTC算法。输入使用两个函数的信息,这两个函数从它们的终端条件沿时间的相反方向计算。控制和外生输入使用状态信息。状态观测器使用系统的输出来估计状态。数值仿真实例显示了输出估计对期望值的跟踪控制特性以及控制和外生输入估计的特性。对于恒定扰动衰减水平γ的无穷大值,本文提出的h -∞线性QTC算法简化为线性QTC算法。对于γ的最小值可以求解的问题是h -∞线性QTC问题。当小于γ的最小值时,h -∞线性QTC算法发散。
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New H-Infinity Tracking Control Algorithm in Linear Discrete-Time Systems
This paper proposes a new H-infinity quadratic tracking control (QTC) algorithm in linear discrete-time systems. This algorithm is a counterpart of the H-infinity QTC algorithm in linear continuous-time systems based on the integral equation approach. The discrete-time state equation in this paper has the control and exogenous inputs. Theorem 1 shows that the control and exogenous inputs in the H-infinity linear QTC problem are given by solving the two-point boundary value problem (TPBVP). Based on the TPBVP, Theorem 2 presents the H-infinity linear QTC algorithm for the control and exogenous inputs. The inputs use the information of two functions, which are calculated in the reverse direction of time from their terminal conditions. The control and exogenous inputs use the information of the state. The state observer uses the output of the system to estimate the state. A numerical simulation example shows the tracking control characteristics of the output estimate to the desired value and the characteristics of the estimates of the control and exogenous inputs. For the infinite value of the constant disturbance attenuation level γ, the proposed H-infinity linear QTC algorithm reduces to the linear QTC algorithm. The problem that can be solved for the minimum value of γ is the H-infinity linear QTC problem. For smaller value than the minimum value of γ, the H-infinity linear QTC algorithm diverges.
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CiteScore
0.20
自引率
14.30%
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0
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