基于预测器的反控制对离散时间变量时间线性状态延迟系统,通过状态过渡矩阵通过明确的输入延迟进行预测
IEEE transactions on cybernetics
|March 18, 2025
概括
本研究涉及对具有状态延迟和明显输入延迟的离散时间系统的稳定. 一个新的基于预测器的反定律有效地稳定了这些复杂的系统,通过数值示例来验证.
科学领域:
- 控制系统工程 控制系统工程
- 系统理论 系统理论
- 应用数学 应用数学 应用数学
背景情况:
- 有状态延迟的离散时间变量线性系统存在重大控制挑战.
- 显著的输入延迟进一步使稳定问题复杂化,需要先进的控制策略.
研究的目的:
- 开发一种稳定离散时间变量时间延迟的线性状态延迟系统的方法,具有明显的输入延迟.
- 为实现系统稳定设计基于预测器的反定律.
主要方法:
- 使用状态过渡矩阵构建一个简洁而明确的预测器.
- 基于拟议的预测方案设计基于预测器的反定律.
- 对闭环系统特征方程的分析.
主要成果:
- 一个新的预测器被开发为离散时间时间变量线性状态延迟系统与不同的输入延迟.
- 基于预测器的反定律成功地稳定了所考虑的系统.
- 对于时间不变系统,特征方程与没有明显输入延迟的系统相匹配.
结论:
- 拟议的基于预测器的反定律有效地稳定了具有明显输入延迟的离散时间变量时间线性状态延迟系统.
- 该方法为复杂的控制场景提供了可靠的解决方案.
- 数字示例证实了该方法的实际适用性和有效性.
更多相关视频
06:45Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
Published on: October 28, 2022
1.5K
10:51An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
Published on: March 10, 2011
13.7K
相关概念视频
Feedback control systems
262
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
262
Transient and Steady-state Response
132
In control systems, test signals are essential for evaluating performance under various conditions. The ramp function is effective for systems undergoing gradual changes, while the step function is suitable for assessing systems facing sudden disturbances. For systems subjected to shock inputs, the impulse function is the most appropriate test signal.
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state...
These test signals are integral in designing control systems to exhibit two key performance aspects: transient response and steady-state...
132
Time-Domain Interpretation of PD Control
77
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
Consider the example of control of motor torque. Initially, a positive...
77
State Space Representation
157
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Consider an RLC circuit, a...
157
Transfer Function to State Space
181
State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
In an...
In an...
181
State Space to Transfer Function
162
The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
162
