Hybrid Model Predictive Control Application Towards Optimal Semi-Active Suspension

By Nicolò Giorgetti, Alberto Bemporad, H. E. Tseng, Davor Hrovat. Proceedings of the IEEE International Symposium on Industrial Electronics, 2005. ISIE 2005., 2005

215 citations recorded by the source corpus.

Subfields: Automotive Engineering, Civil and Structural Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/a20963f905a8599062cb2c42a390570cbf842feb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Francesco Borrelli
2. Lei Zuo
3. Xiudong Tang
4. Manfred Morari

In Civil and Structural Engineering

1. Xiudong Tang
2. Lei Zuo

In Mechanical Engineering

1. Xiudong Tang
2. Lei Zuo

Citations in the corpus

• Large-scale vibration energy harvesting (2013, methodology): “Giorgetti et al. (2006) proposed another method for the semi-active suspension control, where the quarter-car model and the constraints of the semi-active control is modeled into a hybrid dynamical systems and Modeling Predictive Control (MPC) is used for the controlled design.”
• Predictive Control for Linear and Hybrid Systems (2017, background): “Hybrid systems arise in a large number of application areas and are attracting increasing attention in both academic theory-oriented circles as well as in industry, for instance in the automotive industry [16, 157, 62, 125, 74, 214].”
• MPC-Based Approach to Active Steering for Autonomous Vehicle Systems (2005, methodology): “By following a similar approach of the works of (Borrelli et al., 2001; Giorgetti et al., 2005a,b) in the automotive field, the model equations (10) can be piecewise-linearized.”