Extensive advancements in the field of mobility and safety in transportation in last few decades
have acted as a catalyst for the expansion of automobile industry. The research for the evolution
of new technologies, vehicle safety regulations and specifications and the market requirements
has given this progress a greater push. The passenger cars these days are equipped with ample
collection of active safety systems such as Anti-lock Braking Systems (ABS), Electronic Stability
Program (ESP), Active Front Steering (AFS) and many more. The amalgamation of these active
safety systems in the vehicle chassis allows the vehicle to accomplish the desired stability.
Both academia and industry understood the requirement of more research in the field of vehicle
industry. This leads to the comprehensive enhancement in the field of research and development
with respect to integrated chassis control (ICC). The new research delivered some remarkable advantages
to this industry, such as cost reduction of the complete system, multi-objective performance
growth, hardware entanglement, fault-tolerant capability and system plausibility.
Despite the huge diversity in research of integrated chassis, there are certain adaptive design methods
which can be used to enhance the ICC performance. This dissertation intends to provide a
methodology to fully exploit the nonlinear dynamics of the vehicle concerning the forces in between
tire and road surface and to discuss the integration of AFS and ESP. It establishes a novel
adaptive control approach in order to attain asymptotic tracking for switched affine vehicle models
with parameter uncertainties and disturbances acting on the model. This, therefore, will help
to attain the desired performance. Further, comparisonwith strategies that merely exploits the linear
region of the vehicle dynamics are discussed, and performance improvements of the proposed
methodology are assessed. Finally, analytically the endurance of the prospective control strategy
is proven and simulations are conducted to validate the theoretical analysis.

Automated driving, one of the rapidly growing research topics in the field of smart traffic, has proved to be a recognized solution for potentially improving road throughput and reducing vehicles' energy consumption by grouping individual vehicles into platoons controlled by one leading vehicle.

The advances in distributed inter-vehicle communication networks have stimulated a fruitful line of research in Cooperative Adaptive Cruise Control (CACC). In CACC, individual vehicles, grouped into platoons, must automatically adjust their own speed using on-board sensors and communication with the preceding vehicle so as to maintain a safe inter-vehicle distance. The importance of CACC lies in the fact that it enables small inter-vehicle time gaps, which leads to a major reduction of the aerodynamical drag force applied on vehicles in such a driving pattern. Consequently, vehicle emissions, which play a main role in trucks and heavy automobiles, are expected to be highly reduced.

However, a crucial limitation of the state-of-the-art research in this control scheme is that the string stability of the platoon can be proven only when the vehicles in the platoon have identical driveline dynamics and perfect engine performance (homogeneous platoon), and possibly an ideal communication channel.

Thus, the objective of this MSc thesis is to address the problem of CACC for heterogeneous platoons under realistic inter-vehicle network conditions. In the first part, we propose a novel CACC strategy that overcomes the homogeneity assumption and that is able to adapt its action and achieve string stability for uncertain heterogeneous platoons under ideal inter-vehicle network conditions. In the second part, in order to handle the inevitable communication losses, we formulate an extended average dwell-time framework and design an adaptive switched control strategy which activates an augmented CACC or an augmented Adaptive Cruise Control strategy depending on communication reliability.

Stability of the proposed control strategies is proven analytically and simulations are conducted to validate the theoretical analysis.

Major advancements over the last few decades in communication networks gave rise to the
new paradigm of Networked Control Systems (NCSs). Within this paradigm, sensing and
actuation signals are exchanged among various parts of a single system or among many
subsystems via communication networks. Although this enables one to perform more complex
tasks than traditional control paradigms, it comes at the cost of complicating the design phase
and the required analysis tools. One of the major challenges when considering a network is
quantization effect which affects the performance of any control laws that were designed
without taking the network effects into account.
Even if the NCS paradigm is well established, few works are available on adaptive methods for
NCSs: this MSc thesis establishes novel adaptive control approaches that attain asymptotic
tracking for linear systems and switched linear systems with parametric uncertainties, when
input measurements are quantized due to the presence of a communication network closing
the control loop. In addition to enlarging the class of systems for which the adaptive quantized
control can be solved, a hybrid control policy is applied to a novel dynamic quantizer with
dynamic offset to address the tracking problem.
The MSc thesis is split into two parts: in the first part we consider the model reference
adaptive control of a linear uncertain system, where a Lyapunov-based approach is used to
derive the adaptive adjustments for the dynamic range, the dynamic offset and the control
parameters. In the second part, the approach is extended to switched uncertain linear systems
with dwell-time switching, where a new time-varying Lyapunov-like function is adopted: it
is proven analytically that the new Lyapunov function we introduce, overcomes the need
for zooming-out at every time instant in order to compensate the possible increment of the
Lyapunov function.
The proposed quantized adaptive control schemes are applied to two benchmark examples:
an electro-hydraulic system and the piecewise linear model of the NASA GTM aircraft, respectively.