Non-Linear Estimation using the Weighted Average Consensus-Based Unscented Filtering for Various Vehicles Dynamics towards Autonomous Sensorless Design
Authors: Bambang L. Widjiantoro, Moh Kamalul Wafi, Katherin Indriawati
AI-generated Key Points
- Autonomous vehicles raise concerns about coping with environmentally dynamic non-linear systems under constraints and disturbances
- These vehicles are connected to their own instruments and components in their neighborhoods, creating diverse interconnected communications that need to be handled locally for faster decision-making
- Distributed estimation is used to reach untouched states, pursuing sensorless design
- Modified pseudo measurement is constructed to lead to weighted average consensus calculation within unscented filtering along with bounded estimation errors
- Proposed algorithm is tested on various robust control scenarios subject to noise and disturbance, with stability analysis ensuring its effectiveness
- Numerical instances are presented along with the performances of the control and estimation method, which affirms its effectiveness with limited error deviation compared to other centralized and distributed filtering methods
- Study weighs the performances of the estimation according to reviews of distributed estimation and various applications in terms of non-linear uncertainties interconnected system and Pareto optimization
- Results from arbitrary initial conditions highlight convergence almost identical as the reference (r)
- Further research is suggested for directed sensorless design and fault-tolerant learning control subject to faults that negate failures.
- Overall, this study presents a novel approach for non-linear estimation using weighted average consensus-based unscented filtering for various vehicle dynamics towards autonomous sensorless design. The results demonstrate its effectiveness in dealing with interconnected networks while providing insights into future research directions for improving fault tolerance in autonomous vehicles.
Abstract: The concerns to autonomous vehicles have been becoming more intriguing in coping with the more environmentally dynamics non-linear systems under some constraints and disturbances. These vehicles connect not only to the self-instruments yet to the neighborhoods components, making the diverse interconnected communications which should be handled locally to ease the computation and to fasten the decision. To deal with those interconnected networks, the distributed estimation to reach the untouched states, pursuing sensorless design, is approached, initiated by the construction of the modified pseudo measurement which, due to approximation, led to the weighted average consensus calculation within unscented filtering along with the bounded estimation errors. Moreover, the tested vehicles are also associated to certain robust control scenarios subject to noise and disturbance with some stability analysis to ensure the usage of the proposed estimation algorithm. The numerical instances are presented along with the performances of the control and estimation method. The results affirms the effectiveness of the method with limited error deviation compared to the other centralized and distributed filtering. Beyond these, the further research would be the directed sensorless design and fault-tolerant learning control subject to faults to negate the failures.
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