In this thesis a model reference adaptive sliding mode control scheme is proposed for a class of linear time-invariant MIMO systems with unstructured and input, output uncertainties to solve the robust tracking problems. The designing of the proposed control scheme is divided into three steps. The first step is to design the sliding functions, the second step is to construct the estimators of the lumped perturbation. These estimators are able to estimate the derivatives of the tracking errors. The third step is to design the adaptive sliding mode controller. The proposed control scheme is designed without requiring the information of the upper bound of perturbations, and guarantee the stability of the controlled system. In fact the asymptotical stability can be achieved for some special cases. Finally, three numerical examples are presented to demonstrate the feasibility of the proposed control scheme.

Two different perturbation estimation methodologies are compared in this thesis. One is time delay method (TDM), the other is sliding mode techniqueli (SMT). When analyzing the TDM, Pade approximation is used to approximate a function with time-delay argument. The comparisons of perturbation estimation accuracy resulted from TDM and SMT both in time domain and frequency domain are addressed, and two numerical examples are also given for demonstration.

In position control systems like linear motor, friction is a key factor to influence the control performance when micron or sub-micron meter accuracy is required. To overcome the effect of the friction, besides a general model of the linear motor system, past researches have shown an additional static friction model of the system is necessary for a better control performance when the motor move into the micro region of the system (usually <100£gm). Two models, macro and micro model of the system have been well constructed by two different identification methods. After model construction, two different controllers are also designed for each model. A traditional pole-placement PID controller can be easily obtained for the macro model to move into the micro region quickly and stably. Then in micro model design, from the experiments, it is found that system parameter varies and thus degrades the positioning performance of the system. So, a Sliding-Mode Controller is designed to improve these problems. With a two step control strategy, macro and micro step, the linear motor positioning system can achieve a 0.1£gm accuracy within 0.2 sec.

The brightness variance, caused by relative velocity of the camera and environment in a sequence of images, is called optical flow. The advantage of the optical-flow-based visual servo method is that feature of the object dose not need to be known in advance. Therefore, it can be applied for positioning and tracking implement tasks. The purpose of this thesis is to implement the image servo technique and the sliding-mode control method to track an unknown image pattern in three dimensional motion. The goal of tracking is to maintain identical image captured by the camera based on the relative movement calculated from the optical flow.

Based on the Lyapunov stability theorem, two adaptive variable structure control (AVSC) schemes with perturbation estimation are proposed in this thesis for two different classes of nonlinear systems with model uncertainties and external disturbance, so that the robust tracking problems can be solved. The class of systems firstly considered is the one which has square input matrix gain, the other is the one which has non-square input matrix and an output function. All systems considered contain perturbation in the input matrix gain. By introducing a perturbation estimation process embedded in both proposed control schemes, not only the perturbation can be estimated, but also the control energy can be reduced. In addition, the proposed control schemes also contain an adaptive mechanism in order to automatically adapt the unknown upper bound of perturbation estimation error, so that the property of uniformly ultimate boundedness for the closed-loop system is guaranteed. Finally, four numerical examples are presented to demonstrate the feasibility of the proposed control schemes.

In this dissertation three robust control strategies are proposed for a class of multi-input multi-output dynamic systems with matched or mismatched perturbations. Firstly, an adaptive variable structure observer and controller are introduced for solving the regulation problems, where some state variables are not measurable. By utilizing adaptive mechanisms in the design of sliding mode controller, one can enable the controlled systems not only to generate a reaching mode in finite time, but also to suppress the mismatched perturbations during the sliding mode. Secondly, the design of adaptive sliding mode controllers with application to robot manipulators is presented to solve the tracking problems. The dynamic equations of the controlled systems contain a perturbed leading coefficient matrix and can be either positive definite or negative definite. The asymptotical stability of the controlled systems will be attained if the proposed control scheme is employed. Thirdly, a design methodology of adaptive sliding mode controller based on T-S fuzzy model is proposed to solve tracking problems. It is shown that the trajectories of the controlled systems can be driven into a designated sliding surface in finite time, and the property of asymptotical stability is also guaranteed. All these three control schemes are designed by means of Lyapunov stability theorem. Each control scheme contains three parts. The first part is designed for eliminating measurable feedback signals. The second part is used for adjusting the convergent rate of state variables (or tracking errors) of the controlled system. The third part is the adaptive control mechanism, which is used to adapt some unknown constants of the least upper bounds of perturbations, so that the knowledge of the least upper bounds of matched or mismatched perturbations are not required. Several numerical examples and an application of controlling robot manipulator are demonstrated for showing the feasibility of the proposed control methodologies.

The main focus of about this thesis is to design an anti-interference depth controller for underwater remotely operated vehicles(ROV). Since the underwater remotely operated vehicle experiences combination effects of nonlinearities, uncertain and time-varying parameters, and unknown disturbances, demand of robustness for the controller needs to be extremely strict. Therefore, an anti-interference depth controller using PID control and Sliding-mode control is developed. The Matlab simulation tool is employed to simulate the depth control performance of the behavior of the ROV. The simulation is also considered about the model uncertainty of ROV.

Based on the Lyapunov stability theorem, an adaptive variable structure observer and a controller are proposed in this thesis for a class of mismatched perturbed multi-input multi-output (MIMO) dynamic systems with unmeasurable states to solve regulation and tracking problems. In order to estimate the unmeasurable states, a design methodology of variable structure observers is presented first. Then the controller is designed so that the trajectories of the controlled systems are able to reach sliding surface in a finite time. Some adaptive mechanisms are embedded in the sliding surface function and sliding mode controllers, so that not only the mismatched perturbations are suppressed effectively during the sliding mode, but also the information of upper bounds of some perturbations are not required. When the controlled system is the sliding mode, the stability or asymptotical stability is guaranteed. A numerical example and a practical example are given to demonstrate the feasibility of the proposed design technique.

Cooling fans, widely used in desktop and laptop computers, have been designed toward the tendency of low noise and low consumption power. This thesis purposes a efficient low-noise double-loop control method to regulate the fan speed according to environmental temperature. The proposed controller consists of three parts. The first part is a command generator which generates a train of pulses with its frequency varying proportionally with temperature. The second part is a phase locked loop which intends to synchronize the command pulses with the pulses fed back from the Hall IC of the motor. The third part is an inner loop quantized control that switches the fan according to the error signal sent by the phase locked loop. This double-loop design of feedback achieves accurate fan speed regulation with the nice properties of low noise and high efficiency. The experimental results show an average regulation error of 0.4188% in the fan speed range of 306.6~1953 R.P.M which corresponds to the temperature range 10~70 Celsius.

This thesis presents a comparison of controller designs and a system software design for a general Guidance, Navigation and Control (GNC) system. The first part of the thesis investigates four control algorithms based on Lyapunov Direct Method in conjunction with sliding mode and adaptive control. These algorithms address three practical issues in controller design: maximum actuation limitation, external disturbances, and imperfect dynamic models. Each of the algorithms is proven to be globally asymptotically stable within its constraints. A simulation is then used to model a cube-satellite attitude maneuver using each of the controllers to evaluate its performance. The second part of this thesis discusses the development of a high-level flight software architecture capable of handling common tasks, including ground station communication and attitude maneuvers, as well as power or device failures. / text