This research presents an investigation to actively improve the rollover stability of articulated heavy vehicles (AHVs) during high speed manoeuvres using anti-roll control systems. A 3-dimensional (3-D) linear yaw/roll model with 5 degrees of freedom is developed. Based on this model a linear quadratic regulator (LQR) controller is designed to improve the rollover stability of a tractor/semi-trailer combination. A design optimization method for AHVs using genetic algorithms (GAs) and multibody vehicle system models is also presented. AHVs have poor manoeuvrability when travelling at low speeds on local roads and city streets. On the other hand, these vehicles exhibit unstable motion modes at high speeds, including jack-knifing, trailer sway and rollover. From the design point of view, the low-speed manoeuvrability and high-speed stability have conflicting requirements on some design variables. The design method based on a GA and a multibody vehicle dynamic package, TruckSim, is proposed to coordinate this trade-off relationship. To test the effectiveness of the design method, a tractor/semi-trailer combination is optimized using the proposed method. It is demonstrated that the proposed design method can be used for identifying desired design variables and predict performance envelopes in the early design stages of AHVs. / UOIT

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In this thesis, an optimal multivariable current control method is presented for the highspeed permanent magnet synchronous motor (HS-PMSM). The HS-PMSMs have growing applications in the industry. One of their major challenges is the low switching to fundamental frequency ratio (SFR). At high speed and low SFR, the control time delays including the digital, the PWM, and sensor delays become more pronounced and lead to oscillations and even instabilities. A well-known method for delay compensation is to advance the phase angle of control input for a known amount. In practice, the exact delay is unknown, and mismatch in the compensating angle causes deteriorating effect on the system. In the proposed method, the digital and PWM delays are modelled and integrated with an optimal multivariable controller. This method improves the stability margin and achievable speed margin compared to the traditional phase advancing delay compensation (PADC) method. Combining the proposed delay modeling and the PADC method further improves the response, as the uncertain sensor delays can be compensated greatly. Besides the delay, the cross-coupling between ���� axis affects the dynamic performance of the machine. The proposed multivariable approach considers and directly addresses the coupling. Dynamic performance of the PMSM with the proposed method is thoroughly compared with the conventional delay compensation method. The proposed method is validated through extensive simulation studies on a 2 kW high-speed machine.

In this thesis, control and guidance algorithms for unmanned sea surface vehicles are studied. To design control algorithms of different complexity, first a mathematical model for an unmanned sea surface vehicle is derived. The dynamical and kinematical equations for a sea surface vehicle are obtained, and they are adapted to real life conditions with necessary additions and simplifications. The forces and torques effecting on the vehicle are investigated in detail. Control algorithms for under-actuated six degrees-of-freedom model are designed. PID and LQR controllers are implemented to attain desired surge speed and yaw position. The autopilots are designed and their performances are compared. Based on the autopilots, a guidance algorithm is implemented to achieve desired motions of the vehicle. An obstacle avoidance algorithm is proposed for safe motion among the obstacles. A next-point generation algorithm is designed to direct the vehicle to the most appropriate next way-point if the one ahead is missed. The effects of disturbances on the motion of the vehicle are studied thoroughly on simulation results. PID controller for an unmanned sea surface vehicle is implemented on ArduPilot Mega v1.4 cart controlling a Traxxas Spartan model boat. The performance of the controller is validated. Simulations and experimental results are provided.