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This thesis documents the development of a novel nonlinear controller for servo pneumatic actuators that give good reference tracking at low speed motion, where friction has strong effect to the system behaviors. The design of the nonlinear controller presented in this thesis is based on the formalism of Lyapunov stability theory. The controller is constructed through a dynamical adaptive backstepping-sliding mode control algorithm. The conventional Lyapunov-based control algorithm is often limited by the order of the dynamical system; however, the backstepping design concept allows the control algorithm to be extended to higher order dynamical systems. In addition, the friction is estimated on-line via the Lyapunov-based adaptive laws embedded in the controller; meanwhile, the sliding mode control provides high robustness to the system parameter uncertainties. The simulation results clearly demonstrating the improved system performance (i.e., fast response and the reduced tracking error) are presented. Finally, the integration of the controller with a Lyapunov-based pressure observer reduces the state feedback of the servo pneumatic actuator model to only the piston displacement.

This thesis documents the development of a novel nonlinear controller for servo pneumatic actuators that give good reference tracking at low speed motion, where friction has strong effect to the system behaviors. The design of the nonlinear controller presented in this thesis is based on the formalism of Lyapunov stability theory. The controller is constructed through a dynamical adaptive backstepping-sliding mode control algorithm. The conventional Lyapunov-based control algorithm is often limited by the order of the dynamical system; however, the backstepping design concept allows the control algorithm to be extended to higher order dynamical systems. In addition, the friction is estimated on-line via the Lyapunov-based adaptive laws embedded in the controller; meanwhile, the sliding mode control provides high robustness to the system parameter uncertainties. The simulation results clearly demonstrating the improved system performance (i.e., fast response and the reduced tracking error) are presented. Finally, the integration of the controller with a Lyapunov-based pressure observer reduces the state feedback of the servo pneumatic actuator model to only the piston displacement.

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This thesis deals with high angle of attack behaviour of a generic delta wing model aircraft. A high angle of attack wind tunnel database has been generated for this aircraft and based upon the bifurcation analysis of the data and the results of extensive simulations, it has been shown in the thesis that the post stall behaviour of this aircraft is both unstable and unpredictable. Unpredictability of aircraft behaviour arises from the fact that the aircraft response is oscillatory and divergent; the aircraft state trajectories do not settle down to any stable limit set and very often exceed valid aerodynamic database limits. This unpredictability of behaviour raises a major difficulty in the design of a procedure to recover the aircraft to normal flight regime in case the aircraft stalls and departs accidentally. A new methodology has been presented in this thesis to recover such unstable aircraft. In this methodology, a nonlinear controller is first designed at high angles of attack. This controller is connected by the pilot after the departure of the aircraft and the controller drives the aircraft to a well-defined spin condition. Thus, the controller makes the post stall aircraft behaviour predictable. Then a set of automatic recovery inputs is designed to reduce aircraft rotations and to lower the angle of attack. The present aircraft model is unstable at low angle of attack flight conditions as well and therefore to stabilize the aircraft to a low angle of attack level flight, another controller is designed. The high angle of attack controller is disconnected and the low angle of attack controller is connected automatically during the recovery process. The entire methodology is tested using extensive non-linear six degree-of-freedom simulations and the efficacy of the technique is established. The nonlinear controller that stabilizes the aircraft to a spin condition is designed using feedback linearization. The stability of a closed loop system obtained using feedback linearization is determined by the stability of the zero dynamics of the open loop plant. It has been shown in literature that the eigenvalues of the linearized zero dynamics are the same as the transmission zeros of the linearized plant at the equilibrium point. It is also well known that the location of transmission zeros of a linear system can be changed by the choice of outputs. In this thesis it is shown that if it is possible to reassign the outputs, then the feedback linearization based design for a linear system becomes very similar to a controller design for eigenvalue assignment. This thesis presents a new two-step procedure to obtain a locally stable and optimally robust closed loop system using feedback linearization. In the first step of this procedure optimal locations of the transmission zeros are found and in the second step, optimal outputs are constructed to place the system transmission zeros at these locations. The same outputs can then be used to construct nonlinear feedback for the nonlinear system and the resultant closed loop system is guaranteed to be locally robustly stable. The high angle of attack controller is designed using this procedure and its performance is presented in the thesis. The stabilized spin equilibrium point of the closed loop system is also shown to have a large domain of attraction. Having designed a locally robust stabilizing controller, the thesis addresses the problem of the evaluation of robustness of the stability of the equilibrium point in a nonlinear framework. The thesis presents a general method to construct bounds on the additive perturbations of the system vector field over a large region in the domain of attraction of a stable equilibrium point using Lyapunov functions. If the system perturbations lie within these bounds, the system is guaranteed to be stable. The thesis first proposes a method to numerically construct a Lyapunov function over a large region in the domain of attraction. In this method a sequence of Lyapunov functions are constructed such that each function in the sequence gives a larger estimate of the domain of attraction than the previous one. The seminal idea for this method is obtained from the existing literature and this idea is considerably generalized. Using this method, it is possible to numerically obtain a Lyapunov function value at each point in the domain of attraction, but the Lyapunov function does not have an analytical form. Hence, it is proposed to represent this function using neural networks. The thesis then discusses a new method to construct perturbation bounds. It is shown that the perturbation bounds obtained over a large region in the domain of attraction using a single Lyapunov function is too conservative. Using the concept of sequence of Lyapunov functions, the thesis proposes three methods to obtain the least conservative bounds for an initial local Lyapunov function. These general ideas are then applied to the aircraft example and the bounds on the perturbation of the aerodynamic database are presented.

With the increased performance and reduced cost of cameras, the robotics community has taken great interest in estimation and control algorithms that fuse camera data with other sensor data.In response to this interest, this dissertation investigates the algorithms needed for robust guidance, navigation, and control of fixed-wing and multirotor aircraft applied to target estimation and circumnavigation.This work begins with the development of a method to estimate target position relative to static landmarks, deriving and using a state-of-the-art EKF that estimates static landmarks in its state.Following this estimator, improvements are made to a nonlinear observer solving part of the SLAM problem.These improvements include a moving origin process to keep the coordinate origin within the camera field of view and a sliding window iteration algorithm to drastically improve convergence speed of the observer.Next, observers to directly estimate relative target position are created with a circumnavigation guidance law for a multirotor aircraft.Taking a look at fixed-wing aircraft, a state-dependent LQR controller with inputs based on vector fields is developed, in addition to an EKF derived from error state and Lie group theory to estimate aircraft state and inertial wind velocity.The robustness of this controller/estimator combination is demonstrated through Monte Carlo simulations.Next, the accuracy, robustness, and consistency of a state-of-the-art EKF are improved for multirotors by augmenting the filter with a drag coefficient, partial updates, and keyframe resets.Monte Carlo simulations demonstrate the improved accuracy and consistency of the augmented filter.Lastly, a visual-inertial EKF using image coordinates is derived, as well as an offline calibration tool to estimate the transforms needed for accurate, visual-inertial estimation algorithms.The imaged-based EKF and calibrator are also shown to be robust under various conditions through numerical simulation.

Linear switched reluctance motor (LSRM) drives are investigated and proved as an alternative actuator for vertical linear transportation applications such as a linear elevator. A one-tenth scaled prototype elevator focused on a home elevator with LSRMs is designed and extensive experimental correlation is presented for the first time. The proposed LSRM has twin stators and a set of translator poles without back-iron. The translators are placed between the two stators. The design procedures and features of the LSRM and the prototype elevator are described. The designed LSRM is validated through a finite element analysis (FEA) and experimental measurements. Furthermore, a control strategy for the prototype elevator is introduced consisting of four control loops, viz., current, force, velocity, and position feedback control loops. For force control, a novel force distribution function (FDF) is proposed and compared with conventional FDFs. A trapezoidal velocity profile is introduced to control vertical travel position smoothly during the elevator's ascent, descent, and halt operations. Conventional proportional plus integral (PI) controller is used for the current and velocity control loops and their designs are described. The proposed control strategy is dynamically simulated and experimentally correlated. Analytical and experimental results of this research prove that LSRMs are one of the strong candidates for ropeless linear elevator applications. However, the proposed FDF is assuming that the feedback current signals are ideal currents indicating actual phase currents without any measurement disturbances mainly arising from sensor noise, DC-link voltage ripple, measurement offset, and variations in the plant model. Meanwhile, real control systems in industry have measurement disturbance problems. Phase current corrupted by measurement disturbances increases torque or force ripple, acoustic noise and EMI. Therefore, this dissertation also presents a novel current control method to suppress measurement disturbances without extra hardware. The controller is based on an extended state observer (ESO) and a nonlinear P controller (NLP). The proposed method does not require an accurate mathematical model of system and can be implemented on a low-cost DSP controller. The proposed ESO is exploited to estimate the measurement disturbances on measured phase currents, and the proposed NLP compensates for the measurement disturbances estimated by the ESO. The performance of the proposed current control is validated through extensive dynamic simulations and experiments. Moreover, this rejection of measurement disturbances results in a reduction of force ripple and acoustic noise. Due to superior and robust current control performance, it is believed that the proposed method can be successfully applied into other motor drive systems to suppress measurement disturbances with the same promising results without extra hardware. / Ph. D.