Model-Free Disturbance Compensation for Stable MIMO Output Tracking
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Solution Overview
Problem
Existing compact-form model-free adaptive control methods for MIMO systems do not effectively address the issue of compensation control in the presence of measurable disturbances, leading to degradation or instability in control performance.
Innovation Solution
A compact-form model-free adaptive disturbance compensation control method is developed, which involves establishing a dynamic data model using pseudo Jacobian input and disturbance matrices, constructing cost functions, and employing a momentum gradient descent method to optimize control laws, thereby attenuating disturbances and stabilizing the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing compact-form model-free adaptive control methods are used for MIMO systems, then control implementation is simplified, but control performance degrades or becomes unstable in the presence of measurable disturbances
Solution Approach 1:
The control method segments the disturbance compensation by separately estimating disturbance effects for each output channel and compensating them individually in the control law, allowing the system to maintain simplicity while addressing disturbances channel-by-channel
Solution Approach 2:
The method performs preliminary disturbance effect estimation using the dynamic data model and pseudo Jacobian disturbance matrix before applying the control law, enabling proactive compensation that prevents performance degradation rather than reacting to instability
2Reliability
If disturbance compensation control is added to handle measurable disturbances, then control performance stability improves, but system complexity increases
Solution Approach 1:
The system performs self-service by using its own input-output data to automatically build the dynamic data model and estimate disturbance effects without requiring external disturbance measurements or complex disturbance observers, reducing overall system complexity
Solution Approach 2:
The method changes parameters dynamically by updating the pseudo Jacobian input matrix and pseudo Jacobian disturbance matrix online based on recent I/O data, allowing the controller to adapt to changing system conditions without fixed complex structures
3Measurement precision
If dynamic data model with pseudo Jacobian matrices is established, then disturbance estimation accuracy improves, but computational requirements increase
Solution Approach 1:
The method applies partial action by focusing computational effort only on estimating disturbance effects for each output channel separately using simplified pseudo Jacobian matrices, rather than computing full system-wide disturbance models, achieving sufficient accuracy with reduced computation
Data Source
AI summary
A method of compact-form model-free adaptive disturbance compensation control in the presence of measurable disturbances includes establishing a dynamic data model of a controlled plant subject to measurable 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 compact-form model-free adaptive disturbance compensation control law in the presence of measurable disturbances; constructing an energy function and solving it by using a momentum gradient descent method to find optimal values of the compact-form adaptive input matrix and the compact-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.