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An on-line, suboptimal feedback control algorithm is proposed and demonstrated. The procedure is developed using a variational formulation of the optimal control problem. A convex index of performance is presumed. The Finite Element Method is used in conjunction with a variable mesh gridation scheme to produce accurate local approximations of the weak functional forms that result from the variational formulation. These local results provide a basis for the continual updating of the suboptimal control strategy. The extension of the algorithm to the control of nonlinear dynamical systems is also investigated. The Euler Necessary Conditions that describe the analytical solution of the Optimal Control Problem for the nonlinear plant are linearized using two different approaches, Quasilinearization, and Linearization at a Point. The simulated response of both a linear and a nonlinear dynamical system to the input of the suboptimal control generated using the proposed algorithm is offered in plot form. The closure of the disseration includes a suggested list of recommendations for further research. / Ph. D.

The theory of organization that this thesis proposes possesses a characteristic plasticity that should enable it to span the gap that has traditionally existed between the two broad types of current organizational theories. Generally, one type of theory proposes to describe how organizations should function and the other type proposes to describe how organizations actually do function. The first type of theory often seems to result in proposals derived from formal, mechanistic concepts that are necessary, but largely superficial and not profoundly significant in an operational sense. The second type of theory essentially seems to suggest that an “informal organization'' actually functions to achieve the organizational objectives and such an organization is a function of existing personalities and, as a result, no universally applicable principles appear to exist upon which design considerations can be based. Such conclusions are usually drawn from some form of case studies that inherently produce knowledge that proves incomplete and ephemeral as events move on and organizations evolve. Therefore, this theory seeks to reconcile and integrate the basic principles of these two types of theories by conceptualizing the basic principles of engineering design and statistical stability as they apply to organizational processes. / Master of Science

Model predictive control (MPC) has gained great acceptance in the industry since it was developed and first applied about 25 years ago [1]. It has established its place mainly in the advanced control community. Traditionally, MPC configurations are developed and commissioned by control experts. MPC implementations have usually been only worthwhile to apply on processes that promise large profit increase in return for the large cost of implementation. Thus the scale of MPC applications in terms of number of inputs and outputs has usually been large. This is the main reason why MPC has not made its way into low-level loop control. In recent years, academia and control system vendors have made efforts to broaden the range of MPC applications. Single loop MPC and multiple PID strategy replacements for processes that are difficult to control with PID controllers have become available and easier to implement. Such processes include deadtime-dominant processes, override strategies, decoupling networks, and more. MPC controllers generally have more "knobs" that can be adjusted to gain optimum performance than PID. To solve this problem, general PID replacement MPC controllers have been suggested. Such controllers include forward modeling controller (FMC)[2], constraint LQ control[3] and adaptive controllers like ADCO[4]. These controllers are meant to combine the benefits of predictive control performance and the convenience of only few (more or less intuitive) tuning parameters. However, up until today, MPC controllers generally have only succeeded in industrial environments where PID control was performing poorly or was too difficult to implement or maintain. Many papers and field reports [5] from control experts show that PID control still performs better for a significant number of processes. This is on top of the fact that PID controllers are cheaper and faster to deploy than MPC controllers. Consequently, MPC controllers have actually replaced only a small fraction of PID controllers. This research shows that deficiencies in the feedback control capabilities of MPC controllers are one reason for the performance gap between PID and MPC. By adopting knowledge from PID and other proven feedback control algorithms, such as statistical process control (SPC) and Fuzzy logic, this research aims to find algorithms that demonstrate better feedback control performance than methods commonly used today in model predictive controllers. Initially, the research focused on single input single output (SISO) processes. It is important to ensure that the new feedback control strategy is implemented in a way that does not degrade the control functionality that makes MPC superior to PID in multiple input multiple output (MIMO) processes. / text

There are emerging requirements for high accuracy multi-DOF actuators in numerous applications. As one of the novel motors capable of multi-DOF manipulation, permanent magnet spherical motors (PMSMs) that can provide continuous and dexterous motion in one joint have been widely studied for their advantages in structure and energy efficiency. The demands to bring forward the performance of PMSMs for precision applications have motivated this thesis to develop a closed-loop orientation control system with high accuracy and bandwidth. Unlike traditional control methods for PMSMs, which rely on explicit orientation feedback, a new control method (referred to here as direct field-feedback control or in short DFC) directly utilizing the magnetic fields for feedback have been developed in this thesis. Because magnetic field measurements are almost instantaneous and the need for real-time orientation estimation is eliminated in DFC, the system sampling time is greatly reduced. Meanwhile, several field-based methods have been developed for the major components in the DFC system and each component can be processed independently and concurrently with the magnetic field measurements. The parallel computation further improves the system bandwidth and also reduces accumulated error. The DFC system has been experimentally implemented and evaluated. The results show excellent control performances in terms of accuracy and bandwidth. To facilitate the design and analysis of the DFC system, several new algorithms have been developed, which include the modeling and computing of magnetic fields as well as forces and torques, an analysis of bijective relationship between orientation and magnetic fields, and a method for calibration and reconstruction of the rotor magnetic field in 3 dimensional space. These algorithms not only enable the implementation of the DFC system for a PMSM, but also benefit the PMSM studies in design, modeling and field-based sensing. While the immediate outcome of this research is a control system for PMSMs, this new control method can be applied to a broad spectrum of electromagnetic motion systems.

Numerical methods of designing control systems are currently an active area of research. Convex optimization with linear matrix inequalities (LMIs) is one such method. Control objectives like minimizing the H_2, H_infinity norms, limiting the actuating effort to avoid saturation, pole-placement constraints etc., are cast as LMIs and an optimal feedback controller is found by making use of efficient interior-point algorithms. A full-state feedback controller is designed and implemented in this thesis using this method which then forms the basis for designing a static output feedback (SOF) controller. A profile was generated that relates the change in the SOF control gain matrix required to keep the same value of the generalized H_2 norm of the transfer function from the road disturbance to the actuating effort with the change in the sprung mass of the quarter-car system. The quarter-car system makes use of a linear brushless permanent magnet motor (LBPMM) as an actuator, a linear variable differential transformer (LVDT) and two accelerometers as sensors for feedback control and forms a platform to test these control methodologies. For the full-state feedback controller a performance measure (H_2 norm of the transfer function from road disturbance to sprung mass acceleration) of 2.166*10^3 m/s^2 was achieved ensuring that actuator saturation did not occur and that all poles had a minimum damping ratio of 0.2. The SOF controller achieved a performance measure of 1.707*10^3 m/s^2 ensuring that actuator saturation does not occur. Experimental and simulation results are provided which demonstrate the effectiveness of the SOF controller for various values of the sprung mass. A reduction in the peak-to-peak velocity by 73 percent, 72 percent, and 71 percent was achieved for a sprung mass of 2.4 kg, 2.8 kg, and 3.4 kg, respectively. For the same values of the sprung mass, a modified lead-lag compensator achieved a reduction of 79 percent, 77 percent and, 69 percent, respectively. A reduction of 76 percent and 54 percent in the peak-to-peak velocity was achieved for a sprung mass of 6.0 kg in simulation by the SOF controller and the modified lead-lag compensator, respectively. The gain of the modified lead-lag compensator needs to be recomputed in order to achieve a similar attenuation as that of the SOF controller when the value of the sprung mass is changed. For a sprung mass of 3.4 kg and a suspension spring stiffness of 1640 N/m the peak-to-peak velocity of the sprung mass was attenuated by 42 percent.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves [256]-267). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves [256]-267). Also available on the Internet.