# Central Non-Linear Model-Based Predictive Vehicle Dynamics Control
## 5 Conclusions and Outlook  
This contribution presents a central predictive vehicle dynamics control system. The control objectives of an active roll stabilization, a manipulation of the self-steering behavior as well as a reduction of pitching movements are pursued. The control system is \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Setup** & **Driving Maneuver** & **Vehicle Dynamics** & **RMSE** & **Unit** \\ \hline \multirow{8}{*}{Passive Chassis} & \multirow{3}{*}{Double Lane Change} & Roll Behavior & 0.0043 & rad \\  & & Self-Steering Behavior & 8.2703 \(\times 10^{-4}\) & rad \\  & & Pitch Behavior & 0.0114 & rad \\  & & Roll Behavior & 0.0099 & rad \\  & & Self-Steering Behavior & 0.0080 & rad \\  & & Pitch Behavior & 0.0034 & rad \\ \hline \multirow{8}{*}{Perportional Integral Derivative Control and Skyhook Damping} & \multirow{3}{*}{Double Lane Change} & Roll Behavior & 0.0010 & rad \\  & & Self-Steering Behavior & 8.1334 \(\times 10^{-4}\) & rad \\ \cline{1-1}  & & Pitch Behavior & 0.0119 & rad \\ \cline{1-1}  & & Roll Behavior & 0.0031 & rad \\ \cline{1-1}  & & Self-Steering Behavior & 0.0078 & rad \\ \cline{1-1}  & & Pitch Behavior & 0.0035 & rad \\ \hline \multirow{8}{*}{Central Predictive Control} & \multirow{3}{*}{Double Lane Change} & Roll Behavior & 2.3906 \(\times 10^{-4}\) & rad \\ \cline{1-1}  & & Self-Steering Behavior & 8.1009 \(\times 10^{-4}\) & rad \\ \cline{1-1}  & & Pitch Behavior & 0.0106 & rad \\ \cline{1-1}  & & Roll Behavior & 0.0013 & rad \\ \cline{1-1}  & & Self-Steering Behavior & 0.0077 & rad \\ \cline{1-1}  & & Pitch Behavior & 0.0025 & rad \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Central Predictive Vehicle Dynamics Control—Root Mean Squared Errors. implemented by a non-linear model-based predictive control algorithm. The simulation framework comprising a co-simulation between IPG CarMaker and MATLAB & Simulink is used. The test vehicle utilized is a sport utility vehicle equipped with active stabilizers and semi-active dampers to realize the control. Due to the heightened center of gravity, the sport utility vehicle features an increased challenge in influencing rolling and pitching motions. Here, the implementation of active roll stabilization is the primary control objective. The weighting of the control objectives is done via corresponding weighting factors within the optimization of the non-linear model-based predictive control algorithm. The validation is performed for the driving maneuvers of the double lane change and the sinusoidal steering. In conclusion, the implementation of the central predictive control demonstrates an excellent control quality. The central predictive control increases safety and comfort significantly compared to a vehicle with passive chassis elements and a vehicle utilizing a conventional control approach. The focus of this contribution is on the presentation of the central predictive vehicle dynamics control based on the non-linear model-based predictive control algorithm and the resulting excellent control quality. However, due to the numerical solution of the optimization problem, an increased computational effort is imposed at the same time. With regard to a future implementation of the central predictive control, a real-time implementation of this central predictive vehicle dynamics control with a reduced computational effort is required. Whereas classical approaches linearize the underlying prediction models and, thus, simplify them, making them analytically solvable, or limit the iteration steps of the optimization, future work will explore the use of artificial intelligence. Initial conceptual research has already shown a particular suitability of neuro-fuzzy inference systems to address and solve this issue [18]. P.M.S. : conceptualization, methodology, software, validation, formal analysis, investigation, writing and editing, visualization. D.S. : supervision; project administration and critical revision. All authors have read and agreed to the published version of the manuscript.