Finite frequency range robust iterative learning control method for series inverted pendulum

Abstract

The invention discloses a finite frequency range robust iterative learning control method for a series inverted pendulum, and relates to the field of iterative learning control. The method comprises the following steps: building a state-space equation of the series inverted pendulum; converting the state-space equation of the original series inverted pendulum; designing a robust iterative learningcontrol algorithm according to a repetitive process theory; analyzing convergence of a robust iterative learning control algorithm in a limited frequency range; and solving the control law gain of the robust iterative learning control algorithm. The algorithm provided by the invention ensures the stability of the frequency domain of the system and has robust control performance, and ensures the convergence of the output error in the time domain and frequency domain range in the presence of external interference. The system characteristics of the time and operation dimension of the single inverted pendulum subsystem are considered, the method can be directly applied to a series inverted pendulum system composed of multiple inverted pendulum subsystems, good control precision is achieved, and good application value is achieved for verification of the control theory and research of systems with similar structures.

Description

technical field [0001] The invention relates to the field of iterative learning control, in particular to a limited frequency range robust iterative learning control method of a series inverted pendulum. Background technique [0002] The series inverted pendulum is a high-order, strongly coupled, multi-variable unstable complex system, which can intuitively respond to control problems such as nonlinearity, stability and robustness, and is a good device for testing control theory. The series inverted pendulum is composed of several inverted pendulum subsystems with the same structure connected in series, and the inverted pendulum subsystem has an important engineering application background. The stability control of a single-stage inverted pendulum is widely used in attitude control during rocket flight. At the same time, the inverted pendulum is similar to the walking of the biped robot. In daily life, the problem that the center of gravity is up and the fulcrum is down is...

AI Technical Summary

Problems solved by technology

Fuzzy control has strong robustness and fault-tolerant performance, but due to its fuzzy characteristics, the control accuracy and dynamic quality of the system will be reduced.

Neural network control has a strong adaptive ability, but it must have known specific engineering application data samples, and it also needs a long enough time for online or offline learning and training, so its convergence speed is slow

The above control methods have great limitations in the real-time and accuracy of the system, and it is difficult to solve the trajectory tracking problem of the series inverted pendulum

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