# A Survey: Future Smart Cities Based on Advance Control of Unmanned Aerial Vehicles (UAVs)
## 5 Why Nonlinear Control Strategies  
Nonlinear control plays a crucial role in the operation of unmanned aerial vehicles (UAVs) in smart cities. Here are some reasons why nonlinear control is important for UAVs in smart cities:  
* Handling Complex Dynamics: UAVs are highly maneuverable and can perform various tasks such as surveillance, package delivery, and infrastructure inspection. The dynamics of UAVs are inherently nonlinear due to factors like aerodynamics, wind disturbances, and changing payload weights. Nonlinear control techniques allow for more accurate modeling and control of these complex dynamics, enabling precise and efficient UAV operation [84].
* Enhancing Stability and Robustness: Nonlinear control methods can provide stability and robustness to UAVs operating in smart cities. UAVs need to maintain stability under different operating conditions, including varying wind patterns and sudden disturbances. Nonlinear control techniques such as adaptive control and robust control can effectively handle these uncertainties, ensuring stable flight and reliable performance [85].
* Optimizing Control Performance: Smart cities often require UAVs to perform tasks with specific performance objectives. Nonlinear control techniques enable the optimization of control performance by considering factors like energy efficiency, response  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Year** & **Work** & **Short Overview** \\ \hline
1972 & [PERSON] & Theory for dissipative systems [78] \\
1978 & [PERSON] et al. & Model predictive heuristic control [79] \\
19808 & [PERSON] & Formulation of H control [80] \\
1989 & [PERSON] and [PERSON] & Concept of passivity-based control (PBC) [81] \\
1990 & Start & of ’activation process’ \\
1990s & [PERSON] and [PERSON] & Theory of stability [82] \\
1995 & [PERSON] & Geometric control theory [83] \\ \hline \hline \end{tabular}
\end{table}
Table 4: _Cont._  
Figure 6: Limitations of UAV in smart cities.  
time, trajectory tracking, and obstacle avoidance. Adaptive control algorithms can adapt to changing conditions and optimize control parameters in real-time, maximizing the UAV's efficiency and effectiveness [61].
* Dealing with Nonlinear Sensors and Actuators: UAVs rely on sensors for perception and actuation devices for control. Nonlinear control methods can effectively handle the nonlinearities associated with sensors and actuators. This allows for accurate sensor fusion, sensor calibration, and precise actuation, leading to improved reliability and performance of UAV systems in smart cities [61; 84].
* Trajectory Planning and Obstacle Avoidance: UAVs operating in smart cities must navigate complex urban environments while avoiding obstacles and adhering to regulations. Nonlinear control techniques can be used in trajectory planning and obstacle avoidance algorithms to generate feasible and collision-free paths. By accounting for the nonlinear dynamics of UAVs and the surrounding environment, these methods enable safe and efficient navigation in smart city environments [85].
* Fault Detection and Fault-Tolerant Control: In the event of component failures or malfunctions, UAVs need to maintain their control and operation to ensure safety and reliability. Nonlinear control techniques can be utilized for fault detection and fault-tolerant control, enabling UAVs to identify anomalies, adapt their control strategy, and continue operation in a degraded mode. This enhances the resilience of UAV systems in smart cities [86].