Transient Error Normalization for MIMO Control Stability
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Solution Overview
Problem
Multiple Input Multiple Output (MIMO) regulators face challenges in providing optimum stability and dynamic response during large transients due to engine-model mismatches and demand errors, which can lead to suboptimal protection of plant limitations.
Innovation Solution
A method that normalizes control constraints using maximum and minimum constraint normalization processes, calculates a scaling look-up table to adjust control schedules based on normalized transient errors, and applies gain scalars to ensure responses are within engine and plant limits, allowing for smooth transitions between steady state and transient operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If a MIMO regulator is used for control, then stability and dynamic response are improved for steady state and small transients, but control performance deteriorates for large transients due to engine-model mismatches and demand errors
Solution Approach 1:
The patent implements a dynamic gain scheduling mechanism that adjusts controller gains based on the magnitude of the transient error. A normalization process converts the transient error into a scaled value that ranges from small to large, and this scaled value is used to select appropriate gain schedules. This dynamic adaptation allows the MIMO regulator to maintain optimal performance across both small transients and large transients, resolving the contradiction between steady-state stability and large-transient reliability.
Solution Approach 2:
The patent changes the parameter of controller gains based on the operating condition. By introducing gain schedules that are selected based on the normalized transient error magnitude, the system transitions from fixed gains to variable gains. This parameter change enables the regulator to compensate for engine-model mismatches and demand errors during large transients while maintaining stability during steady-state operation.
2Speed
If control gains are increased to improve transient response, then dynamic response is improved, but plant limitation protection deteriorates due to engine-model mismatches
Solution Approach 1:
The patent implements dynamic gain scheduling where the controller gains are adjusted based on the magnitude of the transient error. During large transients, appropriate gain schedules are selected to achieve adequate response speed while preventing excessive control actions that could violate plant limitations. The normalization process ensures that the gain selection is proportional to the error magnitude, providing both fast response when needed and protection when approaching limits.
Solution Approach 2:
The patent pre-calculates and stores multiple gain schedules that are optimized for different transient conditions. These gain schedules are prepared in advance and selected based on the normalized transient error. This preliminary preparation allows the system to quickly switch to appropriate gain settings without real-time computation delays, ensuring both fast transient response and protection of plant limitations.
Data Source
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AI summary
A method and apparatus for providing large transient identification for advanced control with multiple constraints. A request to change a current operating condition of a controlled plant is detected. A value of a control constraint corresponding to the request to change the current operating condition of the controlled plant is determined. A magnitude of a transient error corresponding to the request relative to the value of the control constraint is determined and the current operating condition of the controlled plant is adjusted based on the determined magnitude of the transient error.