Error Compensator Parameter Updating for Vehicle Speed Control
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Solution Overview
Problem
Feedback controllers based on nominal models for vehicle speed control often fail to achieve desired responses due to model errors caused by driving resistance and road gradients, leading to deviations in vehicle speed.
Innovation Solution
A parameter update device and method that acquires input and output data from a vehicle speed control system, calculates a pseudo reference signal, and updates the parameter of an error compensator to minimize an evaluation function, thereby suppressing model errors and achieving desired control responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If feedback control is performed based on a nominal model, then the control system is simple to implement, but model errors cause the vehicle speed to deviate from the target value
Solution Approach 1:
The control system is segmented into three functional modules: a feedback controller that generates basic control input based on the nominal model, an error compensator that calculates correction values to address model errors, and a parameter update device that adapts the compensator parameters. This segmentation allows the system to maintain simplicity while improving accuracy through modular error compensation.
Solution Approach 2:
An error compensator is introduced as an intermediary component between the feedback controller and the control object. This compensator receives the control input from the feedback controller, adds a correction value based on model error estimation, and outputs the final control signal. The intermediary structure enables accuracy improvement without fundamentally changing the simple feedback control architecture.
2Measurement precision
If an error compensator is added to correct model errors, then vehicle speed control accuracy improves, but the device complexity increases
Solution Approach 1:
The error compensator is designed with self-adaptive capabilities through the parameter update device. The system automatically estimates model errors from operational data, updates the compensator parameters without external intervention, and maintains optimal performance autonomously. This self-service mechanism reduces the need for manual tuning and complex external calibration systems.
Solution Approach 2:
The error compensator uses adjustable parameters that are dynamically updated based on observed system behavior. By changing these parameters adaptively rather than fixing them, the compensator can handle varying operating conditions and model uncertainties. This parameter-based approach provides flexibility and accuracy without requiring a completely complex system redesign.
3Measurement precision
If the error compensator parameter is manually tuned, then the control accuracy can be optimized, but it requires time-consuming trial and error and expert knowledge
Solution Approach 1:
The parameter update device implements a feedback mechanism that continuously monitors the difference between actual vehicle speed and target speed, along with the control input and estimated model errors. This feedback information is used to automatically adjust the error compensator parameters, eliminating the need for manual trial-and-error tuning and reducing dependency on expert knowledge.
Solution Approach 2:
The system performs automatic parameter updating without requiring external expert intervention. The parameter update device autonomously processes operational data, estimates model errors, and adjusts the error compensator parameters in real-time. This self-service capability saves significant time and eliminates the need for manual tuning sessions.
Data Source
AI summary
In a control system including a feedback controller, a nominal model, and an error compensator, a parameter update device that updates a parameter of the error compensator 1 includes a data acquisition part that acquires input data indicating a control input to a control object and output data indicating an output from the control object, a reference signal acquisition part that finds a pseudo reference signal, which is a control target value, using the input data and the output data, and a parameter update part that updates the parameter of the error compensator by minimizing an evaluation function defined by the pseudo reference signal.