Pseudo Jacobian Disturbance Compensation for Stable MIMO Control
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Solution Overview
Problem
Existing full-form model-free adaptive control methods for MIMO systems do not effectively address the challenge of compensation control in the presence of unmeasurable disturbances, which can lead to degradation or instability in control performance.
Innovation Solution
A method of full-form model-free adaptive disturbance compensation control is implemented using a dynamic data model described by pseudo Jacobian input and disturbance matrices, with optimization techniques to find optimal values for these matrices, and a momentum gradient descent method to adjust adaptive input and disturbance matrices, resulting in a control law that attenuates unmeasurable disturbances and stabilizes the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full-form model-free adaptive control method is used for MIMO systems, then control performance is improved, but the system becomes vulnerable to unmeasurable disturbances causing degradation or instability
Solution Approach 1:
The patent introduces a disturbance observer as an intermediary component that estimates unmeasurable disturbances based on system inputs and outputs. This observer acts as a mediator between the controlled plant and the controller, providing disturbance compensation signals that improve reliability without requiring direct measurement of disturbances.
Solution Approach 2:
The patent implements a feedback mechanism where the estimated disturbances from the disturbance observer are fed back to the controller. This feedback loop allows the system to continuously compensate for unmeasurable disturbances, maintaining control performance and stability despite the presence of harmful factors.
2Stability of the object's composition
If disturbance compensation control is added to attenuate unmeasurable disturbances, then system stability is improved, but device complexity increases
Solution Approach 1:
The disturbance observer is designed to self-estimate disturbances using only the system's own input-output data without requiring external sensors or complex modeling. This self-service approach provides disturbance compensation while minimizing the addition of external components and complexity.
Solution Approach 2:
The proposed disturbance compensation control method is designed to be universally applicable to MIMO systems with unmeasurable disturbances. The same control framework can handle multiple inputs and outputs simultaneously, providing stability improvement without proportionally increasing complexity through modular design.
Data Source
AI summary
A method of full-form model-free adaptive disturbance compensation control in the presence of unmeasurable disturbances, includes establishing a dynamic data model of a controlled plant subject to unmeasurable disturbances, wherein the dynamic data model is described by a pseudo Jacobian input matrix and a pseudo Jacobian disturbance matrix; constructing cost functions and solving their optimization problems to find optimal values of the pseudo Jacobian input matrix and the pseudo Jacobian disturbance matrix; designing a full-form model-free adaptive disturbance compensation control law in the presence of unmeasurable disturbances; constructing an energy function and solving it by using a momentum gradient descent method to find optimal values of the full-form adaptive input matrix and the full-form adaptive disturbance matrix; controlling the controlled plant by using the control law. The control method of the present invention provides significant improvements in disturbance compensation control performance and achieves effective tracking of desired system outputs.