具有时变非对称约束的不确定非线性系统实际固定时间自适应模糊控制:一种基于统一障碍函数的方法
Practical fixed-time adaptive fuzzy control of uncertain nonlinear systems with time-varying asymmetric constraints:a unified barrier function based approach
黄梓煊 1王焕清 2牛奔 3赵旭东 4Adil M. AHMAD5
作者信息
- 1. 渤海大学控制科学与工程学院,中国 锦州市,121013
- 2. 渤海大学数学科学学院,中国 锦州市,121013
- 3. 山东师范大学信息科学与工程学院,中国 济南市,250014
- 4. 大连理工大学电子信息与电气工程学部,中国 大连市,116024
- 5. 阿卜杜勒·阿齐兹国王大学计算与信息技术学院信息技术系通信系统与网络研究组,沙特阿拉伯吉达
- 折叠
摘要
研究了具有时变不对称约束和输入量化的不确定非线性系统,提出一种实际固定时间自适应模糊控制方法.为消除状态约束对控制器设计的影响,采用一个统一的障碍函数方法将原有约束系统映射为无约束系统,这不仅放松了时变非对称约束对系统状态的限制,而且避免了传统的障碍Lyapunov函数控制方法中的可行性条件检查.同时,利用命令滤波方法解决了传统反步法中的"复杂度爆炸"问题.通过固定时间Lyapunov稳定性判据,证实系统输出能够在预定时间内以较小误差范围跟踪参考信号,并且系统的所有状态保持在约束范围内.最后,通过2个仿真实例验证了所提方法的有效性.
Abstract
A practical fixed-time adaptive fuzzy control strategy is investigated for uncertain nonlinear systems with time-varying asymmetric constraints and input quantization.To overcome the difficulties of designing controllers under the state constraints,a unified barrier function approach is employed to construct a coordinate transformation that maps the original constrained system to an equivalent unconstrained one,thus relaxing the time-varying asymmetric constraints upon system states and avoiding the feasibility check condition typically required in the traditional barrier Lyapunov function based control approach.Meanwhile,the"explosion of complexity"problem in the traditional backstepping approach arising from repeatedly derivatives of virtual controllers is solved by using the command filter method.It is verified via the fixed-time Lyapunov stability criterion that the system output can track a desired signal within a small error range in a predetermined time,and that all system states remain in the constraint range.Finally,two simulation examples are offered to demonstrate the effectiveness of the proposed strategy.
关键词
统一障碍函数/时变不对称状态约束/模糊逻辑系统/固定时间控制/指令滤波器Key words
Unified barrier function/Time-varying asymmetric state constraints/Fuzzy logic systems/Fixed-time control/Command filter引用本文复制引用
出版年
2024
NETL
NSTL
万方数据