# A Survey: Future Smart Cities Based on Advance Control of Unmanned Aerial Vehicles (UAVs)
## 6 Importance of Hybrid Control Techniques
\begin{table}
\begin{tabular}{c c c} \hline
**Year** & **Contributor** & **History** \\ \hline
1980s & [PERSON] and [PERSON] & They introduced the concept of hybrid systems and proposed a framework for analyzing their behavior [103; 117; 118]. \\ \hline
1990s & [PERSON], [PERSON]. & There have been numerous advances in hybrid control theory, with many researchers contributing to the field. One of the significant milestones in hybrid control theory was the development of the hybrid automaton model, which is a formalism for representing and analyzing hybrid systems[116; 119]. \\ \hline
1995 & [PERSON] and & Other important contributions to hybrid control theory include the development of control synthesis methods, which are used to design control strategies for hybrid systems, and the study of stability and performance properties of hybrid systems [120]. \\ \hline
2008 & [PERSON], [PERSON] and & Another significant contribution to hybrid control theory is the development of reachability analysis methods, which are used to determine the set of states that a hybrid system can reach from a given initial state. These methods have been shown to be effective for analyzing the behavior of hybrid systems and designing control strategies for them [121; 122]. \\ \hline \end{tabular}
\end{table} 
Table 6: Hybrid control. stabilization refers to the control of the UAV's orientation or angular position, while position control refers to the control of the UAV's position in space. The authors suggest using a linear control approach for attitude stabilization, which typically involves using mathematical models and techniques to stabilize the UAV's orientation. Linear control approaches are often effective for small deviations from the desired attitude [104]. The results showed that the hybrid controller achieved better performance compared to the individual controllers. Another example is the paper [105; 106; 126], in which the authors proposed a hybrid controller that combines a linear control approach for attitude stabilization and a nonlinear control approach for position control. The experimental results showed that the hybrid controller achieved better performance in terms of tracking accuracy and disturbance rejection compared to the individual controllers. The paper introduces a hybrid control system for a quadcopter drone's trajectory tracking. Combining traditional PD control with fuzzy logic, the hybrid approach enhances robustness to uncertainties. Both controllers work in parallel to improve performance and robustness. Computer simulations and real-flight tests demonstrate their effectiveness against parameter variations, nonlinear aerodynamics, and disturbances like wind gusts. The hybrid system's stability is analyzed using [PERSON]'s method [108]. This study addresses robust control design for uncertain conditions, focusing on precise trajectory tracking for a small quadcopter UAV. It presents a hybrid feedback and feedforward autopilot system to counter disturbances in vertical, lateral, and longitudinal loops, as well as external factors like wind gusts. By combining nonlinear model predictive control and a fuzzy feedforward compensator, the hybrid system enhances performance beyond traditional PD control. Comparative studies showcase its effectiveness, and stability analysis ensures reliable operation [108]. Many studies have focused on asymptotic and exponential stability, where errors converge as time approaches infinity. However, this approach may not always be ideal as quick response and convergence of error states within a few seconds are desired. Consequently, only a limited number of studies in the literature have addressed finite-time convergence in flight control systems. After the comprehensive literature regarding the deployment of UAVs in smart cities, the merits and demerits of nonlinear hybrid control strategies are elaborated in Table 7. Hybrid control theory plays a significant role in enhancing the functionality and efficiency of UAVs within the framework of smart cities.