The quadrotor unmanned aerial vehicle is a great platform for control systems research as its nonlinear nature and under-actuated configuration make it ideal to synthesize and analyze control algorithms. After a brief explanation of the system, several algorithms have been analyzed including their advantages and disadvantages: PID, Linear Quadratic Regulator (LQR), Sliding mode, Backstepping, Feedback linearization, Adaptive, Robust, Optimal, L1, H∞, Fuzzy logic and Artificial neutral networks. The conclusion of this work is a proposal of hybrid systems to be considered as they combine advantages from more than one control philosophy.

Antilock Brake System (ABS) controller maintains or controls the slip between tyre and road to maximize the braking torque to achieve a shorter braking distance and control of the steering wheel. This paper presents a PID slip controller performance that incorporates nonlinear passive suspension dynamics. Three scenarios were compared The first scenario is the performance of the controller in a vehicle model without any suspension dynamics, the second scenario incorporates linear passive vehicle suspension system (LPVSS) and the third scenario incorporates nonlinear passive vehicle suspension system (NLPVSS). The incorporation of the passive suspension dynamics enhanced the ABS performance.

Continual improvement of the anti-lock braking system control strategy is the focus of this work. Advances in auto-electronics and sub-systems such as the brake-by-wire technology are the driving forces behind the improvement of the anti-lock braking system. The control strategy has shifted from speed-control to slip-control strategy. In the current slip-control approach, proportional-integral-derivative (PID) controller and its variants: P, PI and PD have been proposed in place of the bangbang controller mostly used in commercial ABS. Though the PID controller is famous due to its wide applications in industry: irrespective of the nature of the process or system, it might lead to limited performance when applied to the ABS. In order to improve the performance of the PID controller, a neural network inverse model of the plant is used to optimize the reference input slip. The resultant neural network-based PID ABS is then tested in Matlab R /Simulink R simulation environment. The results of the proposed controller, exhibits more accurate slip tracking than the PID-slip controller.

The commercial Bang-Bang anti-lock braking system has several short-comings. Therefore, there is the need for continual improvement on the ABS control strategy. One of the problems associated with these short-comings includes the physical shock experienced by drivers through the brake petal pulsation, when the system is activated. A non-linear and a neural network-based alternative ABS control schemes are proposed and evaluated. The main goal is for the ABS controller to maintain optimal system performance in terms of slip regulation and minimising the vehicle stopping distance during hard-braking. A comparative analysis of the two ABS controllers based on simulation results, showed the neural network-based controller to be superior.

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