Integrated Design and Efficient Safe Control for Terrain- Adaptive Ultra-lightweight Vehicles

Principal Investigators

• Zhaojian Li (PI), Wei-Che Tai, Vaibhav Srivastava (co-PI), Michigan State University

Students

• Majid Mazouchi (Postdoc), Van Duong, Richard Lin, Mohammad Hajidavalloo, Logan Roeser-Nordling, Henry Kantzes, Michigan State University

Government

• Jill Goryca, US Army GVSC

Project duration Q4 2022 through 2024.

Achieving robust and efficient stability control of the ultra-lightweight vehicle in the presence of uneven terrains poses several challenges that may not be addressed by current state-of-the-art techniques [1,2]. This challenge is further exacerbated by the current narrow-body, lightweight designs, which are prone to accidents from rollovers and flip-overs. The mechanical design and control synthesis of vehicle stability systems have largely been conducted in a sequential or iterative manner where the design and control coupling are neglected. This will inevitably lead to sub-optimal designs. A control co-optimization framework is needed to fully optimize the system, but this is challenging – especially in the presence of parameter constraints and multiple conflicting objectives. Existing vehicle stability control schemes are generally based on a fixed model and thus lack adaptability to changes in system parameters. However, vehicles operating in rough conditions are susceptible to parameter changes and thus it is crucial to empower the stability control system with adaptability and guaranteed safety.

To address the above challenges, we will develop and optimize an off-road active or semi-active suspension system that is energy-efficient but powerful to support challenging driving conditions. We will develop terrain-adaptive vehicle motion controls that systematically integrate an online terrain profile estimation and active disturbance rejection controls to mitigate the impact of uneven terrains. We will also develop effective learning-based active safety control schemes to ensure safe operations for the ultra-lightweight vehicle in an unstructured field environment in the presence of model parameter changes. All these challenges require foundational advance in control technology and our proposed novel design and control paradigms constitute basic research.

The fundamental research questions in this project are:

1. If an ultra-lightweight vehicle can be designed to operate on uneven and rough terrains, maintaining vehicle stability control on those surfaces?
2. How do we address the challenge of driving on uneven terrain that requires novel off-road suspension and steering and control designs that are adequately powerful and energy-efficient?

Publications:

• Majid Mazouchi, Zhaojian Li, Vaibhav Srivastava, Wei-Che Tai, and Jill Goryca, “Learning-Enhanced Active Vehicle Suspension Control Using Preview-augmented Model Predictive Control and Gaussian Process”, 2024 4th Modeling, Estimation and Control Conference
• Mohammad Hajidavalloo, Vaibhav Srivastava, and Zhaojian Li, “Data-Driven Anti-Rollover Control”, to be submitted to IEEE Transactions on Intelligent Transportation System

References [1]. Z.Li,I.V.Kolmanovsky,E.M.Atkins,J.Lu,D.P.Filev,andY.Bai,“Roaddisturbance estimation and cloud-aided comfort-based route planning,” IEEE Transactions on Cybernetics, pp. 1–13, 2016. doi:10.1109/TCYB.2016.2587673. [2]. Z.Li,I.Kolmanovsky,E.Atkins,J.Lu,D.Filev,andJ.Michelini,“Cloudaidedsemi-active suspension control,” in 2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS), pp. 76–83, Dec 2014.

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