<p>The task in this thesis is the steering of one of Saab Bofors Dynamics robots using Sliding Mode Control, a method they never used before. The robot constitutes a system which in addition to perturbations and uncertainties due to modeling imprecision, hold the difficulty of being highly time variant. In order to be able to keep required performance with uncertainties and modeling imprecision present, the use of robust control methods like Sliding Mode Control is necessary. SMC is based on the states of the system being forced to stay on or in the direct vicinity of a hyper plane in the state space which is chosen in a way that gives the system dynamics desired properties. Other advantages with sliding mode are reduced order dynamics on the switching surface and total insensitivity to some uncertainties and perturbations. The existing metod for controlling the robot is Linear Quadratic Control. To evaluate the SMC-methodology and compare it with the existing solution simulations using SMC and LQ-control are made with uncertainties and modeling imprecision. Our tests show that a control law based on SMC is robust and seems to be a very good alternative to the existing solution.</p>

Recently, active suspension has been applied to many commercial automobiles. To develop the control algorithm for active suspension, a quarter-car test bed was built by using a direct-drive tubular linear brushless permanent-magnet motor (LBPMM) as a force-generating component. Two accelerometers and a linear variable differential transformer (LVDT) are used in this quarter-car test bed. Three pulse-width-modulation (PWM) amplifiers supply the currents in three phases. Simulated road disturbance is generated by a rotating cam. Modified lead-lag control, linear-quadratic (LQ) servo control with a Kalman filter, and the fuzzy control methodologies were implemented for active-suspension control. In the case of fuzzy control, asymmetric membership functions were introduced. This controller could attenuate road disturbance by up to 78%. Additionally, a sliding-mode controller (SMC) is developed with a different approach from the other three control methodologies. While SMC is developed for the position control, the other three controllers are developed for the velocity control. SMC showed inferior performance due to the drawback of the implemented chattering-proof method. Both simulation and experimental results are presented to demonstrate the effectiveness of these four control methodologies.

This thesis is to deal with the saturation problem arisen from the integrator accumulation in the loop of the sigma-delta analog-to-digital converter. Signal passes through the accumulation of several integrators in the high-order sigma-delta analog-to-digital converter, it tends to result in saturation problem in the output of integrator. This phenomenon is prominent especially in implementation. Unable to correctly propagate signal to the next integrator stage, thus, causes the analog-to-digital converter create incorrect result. Accordingly, this thesis proposes a new anti-windup scheme by means of sliding mode control to tackle the saturation problem. We have successfully set up a criterion for the selection of parameters of the sigma-delta analog-to-digital converter to prevent the integrators from saturation. After extensive simulation and experiment, it can significantly improve the ensemble of the sigma-delta analog-to-digital modulator.

It has been well known that the architecture of insect compound eyes contributes outstanding capability for precise and efficient observation of moving objects. If this technique can be transferred to the domain of engineering applications, significant improvement on visual tracking of moving objects will be greatly expected. The brightness variation, 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 methods is that features of the moving object do not have to be known in advance. Therefore, they can be applied for general positioning and tracking tasks. The purpose of this thesis is to develop a visual servo system with trinocular cameras. For mimicking the configuration of compound eyes of insects, the arrangement of the divergent trinocular cameras is applied. In order to overcome possible difficulties of unknown or uncertain parameters, an image servo technique using the robust discrete-time sliding-mode control algorithm to track an object moving in 2D space is developed.

This dissertation discusses an implementation of a design, control and motion planning for a novel extendable modular redundant robotic manipulator in space constraints, which robots may encounter for completing required tasks in small and constrained environment. The design intent is to facilitate the movement of the proposed robotic manipulator in constrained environments, such as rubble piles. The proposed robotic manipulator with multi Degree of Freedom (m-DOF) links is capable of elongating by 25% of its nominal length. In this context, a design optimization problem with multiple objectives is also considered. In order to identify the benefits of the proposed design strategy, the reachable workspace of the proposed manipulator is compared with that of the Jet Propulsion Laboratory (JPL) serpentine robot. The simulation results show that the proposed manipulator has a relatively efficient reachable workspace, needed in constrained environments. The singularity and manipulability of the designed manipulator are investigated. In this study, we investigate the number of links that produces the optimal design architecture of the proposed robotic manipulator. The total number of links decided by a design optimization can be useful distinction in practice. Also, we have considered a novel robust bio-inspired Sliding Mode Control (SMC) to achieve favorable tracking performance for a class of robotic manipulators with uncertainties. To eliminate the chattering problem of the conventional sliding mode control, we apply the Brain Emotional Learning Based Intelligent Control (BELBIC) to adaptively adjust the control input law in sliding mode control. The on-line computed parameters achieve favorable system robustness in process of parameter uncertainties and external disturbances. The simulation results demonstrate that our control strategy is effective in tracking high speed trajectories with less chattering, as compared to the conventional sliding mode control. The learning process of BLS is shown to enhance the performance of a new robust controller. Lastly, we consider the potential field methodology to generate a desired trajectory in small and constrained environments. Also, Obstacle Collision Avoidance (OCA) is applied to obtain an inverse kinematic solution of a redundant robotic manipulator.

The task in this thesis is the steering of one of Saab Bofors Dynamics robots using Sliding Mode Control, a method they never used before. The robot constitutes a system which in addition to perturbations and uncertainties due to modeling imprecision, hold the difficulty of being highly time variant. In order to be able to keep required performance with uncertainties and modeling imprecision present, the use of robust control methods like Sliding Mode Control is necessary. SMC is based on the states of the system being forced to stay on or in the direct vicinity of a hyper plane in the state space which is chosen in a way that gives the system dynamics desired properties. Other advantages with sliding mode are reduced order dynamics on the switching surface and total insensitivity to some uncertainties and perturbations. The existing metod for controlling the robot is Linear Quadratic Control. To evaluate the SMC-methodology and compare it with the existing solution simulations using SMC and LQ-control are made with uncertainties and modeling imprecision. Our tests show that a control law based on SMC is robust and seems to be a very good alternative to the existing solution.

A methodology of designing an adaptive sliding mode controller for a class of nonlinear systems with matched and mismatched perturbations is proposed in this thesis. A specific designed sliding surface function is presented first, whose coefficients are determined by using Lyapunov stability theorem and linear matrix inequality (LMI) optimization technique. Without requiring the upper bounds of matched perturbations, the controller with adaptive mechanisms embedded is also designed by using Lyapunov stability theorem. The proposed control scheme not only can drive the trajectories of the controlled systems reach sliding surface in finite time, but also is able to suppress the mismatched perturbations when the controlled systems are in the sliding mode, and achieve asymptotic stability. In addition, the proposed control scheme can be directly applied to a class of underactuated systems. A numerical example and a practical experiment are given for demonstrating the feasibility of the proposed control scheme.

Based on the Lyapunov stability theorem, a sliding mode control design methodology is proposed in this thesis for a class of perturbed switched systems. The control of the systems is rest restricted to switching between two different constant values. New sliding mode reaching conditions are proposed for the controllers so that the controlled systems can enter the sliding mode in finite time. Once the switched control system is in the sliding mode, the stability of the system is guaranteed by choosing a suitable sliding surface. In addition, a method for alleviating the infinite switching phenomenon is also provided in this thesis. Finally, a numerical and a practical example with computer simulation results are given for demonstrating the feasibility of the proposed control scheme.

Recently, active suspension has been applied to many commercial automobiles. To develop the control algorithm for active suspension, a quarter-car test bed was built by using a direct-drive tubular linear brushless permanent-magnet motor (LBPMM) as a force-generating component. Two accelerometers and a linear variable differential transformer (LVDT) are used in this quarter-car test bed. Three pulse-width-modulation (PWM) amplifiers supply the currents in three phases. Simulated road disturbance is generated by a rotating cam. Modified lead-lag control, linear-quadratic (LQ) servo control with a Kalman filter, and the fuzzy control methodologies were implemented for active-suspension control. In the case of fuzzy control, asymmetric membership functions were introduced. This controller could attenuate road disturbance by up to 78%. Additionally, a sliding-mode controller (SMC) is developed with a different approach from the other three control methodologies. While SMC is developed for the position control, the other three controllers are developed for the velocity control. SMC showed inferior performance due to the drawback of the implemented chattering-proof method. Both simulation and experimental results are presented to demonstrate the effectiveness of these four control methodologies.

The objective of this research is to develop innovative techniques for modeling and control of network congestion. Most existing network controls have discontinuous actions, but such discontinuity in control actions is commonly omitted in analytical models, and instead continuous models were widely adopted in the literature. This approximation works well under certain conditions, but it does cause significant discrepancy in creating robust, responsive control solutions for congestion management. In this dissertation, I investigated three major topics. I proposed a generic discontinuous congestion control model and its design methodology to guarantee asymptotic stability and eliminate traffic oscillation, based on the sliding mode control (SMC) theory. My scheme shows that discontinuity plays a crucial role in optimization of the I-D based congestion control algorithms. When properly modeled, the simple I-D control laws can be made highly robust to parameter and model uncertainties. I discussed applicability of this model to some existing flow or congestion control schemes, e.g. XON/XOFF, rate and window based AIMD, RED, etc. It can also be effectively applied to design of detection and defense of distributed denial of service (DDoS) attacks. DDoS management can be considered a special case of the flow control problem. Based on my generic discontinuous congestion control model, I developed a backward-propagation feedback control strategy for DDoS detection and defense. It not only prevents DDoS attacks but also provides smooth traffic and bounded queue size. Another application of the congestion control algorithms is design of private group communication networks. I proposed a new technique for protection of group communications by concealment of sender-recipient pairs. The basic approach is to fragment and disperse encrypted messages into packets to be transported along different paths, so that the adversary cannot efficiently determine the source/recipient of a message without correct ordering of all packets. Packet flows among nodes are made balanced, to eliminate traffic patterns related to group activities. I proposed a sliding window-based flow control scheme to control transmission of payload and dummy packets. My algorithms allow flexible tradeoff between traffic concealment and performance requirement.