Abstract: NMPC explicitly addresses constraints and nonlinearities during the feedback control of batch processes. This NMPC algorithm also explicitly takes parameter uncertainty into account in the state estimation and state feedback controller designs. An extended Kalman filter estimates the process noise covariance matrix from the parameter uncertainty description and employs a sequential integration and correction strategy to reduce biases in the state estimates due to parameter uncertainty. The shrinking horizon NMPC algorithm minimizes a weighted sum of the nominal performance objective, an estimate of the variance of the performance objective, and an integral of the deviation of the control trajectory from the nominal optimal control trajectory. The robust performance is quantified by estimates of the distribution of the performance index along the batch run obtained by a series expansion about the control trajectory. The control and analysis approaches are applied to a simulated batch crystallization process with a realistic uncertainty description. The proposed robust NMPC algorithm improves the robust performance by a factor of six compared to open loop optimal control, and a factor of two compared to nominal NMPC. Monte Carlo simulations support the results obtained by the distributional robustness analysis technique.

Abstract: The primary focus of study in this paper is the background control theory for automated lane change maneuvers. We provide an analytic approach for the systematic development of controllers that will cause an autonomous vehicle to accomplish a smooth lane change suitable for use in an Automated Highway System. The design is motivated by the discontinuous availability of valid preview data from the sensing systems during lane-to-lane transitions. The task is accomplished by the generation of a virtual yaw reference and the utilization of a robust switching controller to generate steering commands that cause the vehicle to track that reference. In this way, the open loop lane change problem is converted into an equivalent virtual reference trajectory tracking problem. The approach considers optimality in elapsed time at an operating longitudinal velocity. Although the analysis is performed assuming that the road is straight, the generalization of the proposed algorithm to arbitrary road segments is rather straightforward. The outlined lane change algorithm has been implemented and tested on The Ohio State University test vehicles. Some of the experimental results are presented at the conclusion of this paper.

Abstract: In this paper, a modular Simulink implementation of an induction machine model is described in a step-by-step approach. With the modular system, each block solves one of the model equations; therefore, unlike black box models, all of the machine parameters are accessible for control and verification purposes. After the implementation, examples are given with the model used in different drive applications, such as open-loop constant V/Hz control and indirect vector control are given. Finally, the use of the model as an Induction generator is demonstrated.

Abstract: The antilock braking system (ABS) is designed to optimize braking effectiveness and maintain steerability; however, the ABS performance will be degraded in the case of severe road conditions. In this study, a self-learning fuzzy sliding-mode control (SLFSMC) design method is proposed for ABS. The SLFSMC ABS will modulate the brake torque for optimum braking. The SLFSMC system is comprised of a fuzzy controller and a robust controller. The fuzzy controller is designed to mimic an ideal controller and the robust controller is designed to compensate for the approximation error between the ideal controller and the fuzzy controller. The tuning algorithms of the controller are derived in the Lyapunov sense; thus, the stability of the system can be guaranteed. Also, the derivation of the proposed SLFSMC ABS does not need to use a vehicle-braking model. Simulations are performed to demonstrate the effectiveness of the proposed SLFSMC ABS in adapting to changes for various road conditions.

Abstract: This thesis addresses two neural network based control systems. The first is a neural network based predictive controller. System identification and controller design are discussed. The second is a direct neural network controller. Parameter choice and training methods are discussed. Both controllers are tested on two different plants. Problems regarding implementations are discussed. First the neural network based predictive controller is introduced as an extension to the generalised predictive controller (GPC) to allow control of non-linear plant. The controller design includes the GPC parameters, but prediction is done explicitly by using a neural network model of the plant. System identification is discussed. Two control systems are constructed for two different plants: A coupled tank system and an inverse pendulum. This shows how implementation aspects such as plant excitation during system identification are handled. Limitations of the controller type are discussed and shown on the two implementations. In the second part of this thesis, the direct neural network controller is discussed. An output feedback controller is constructed around a neural network. Controller parameters are determined using system simulations. The control system is applied as a single-step ahead controller to two different plants. One of them is a path-following problem in connection with a reversing trailer truck. This system illustrates an approach with step-wise increasing controller complexity to handle the unstable control object. The second plant is a coupled tank system. Comparison is made with the first controller. Both controllers are shown to work. But for the neural network based predictive controller, construction of a neural network model of high accuracy is critical especially when long prediction horizons are needed. This limits application to plants that can be modelled to sufficient accuracy. The direct neural network controller does not need a model. Instead the controller is trained on simulation runs of the plant. This requires careful selection of training scenarios, as these scenarios have impact on the performance of the controller.

Abstract: A new approximate model, which consists of a variable gain and a variable time-delay, is proposed to describe the hysteresis behavior of a piezoactuator. The variable gain is assumed to be a function of the magnitude of the input command, while the time-delay is assumed to be a function of the frequency of the input command. The ranges of these two variable parameters are determined through open loop tests. According to the proposed approximate model, a Smith predictor-based robust H x controller is developed to achieve high-precision tracking control of a piezoactuator. Analytical simulation and experimental results on tracking several types of reference inputs demonstrate that the maximum trucking error can be reduced to be less than 2% of the traveling path by utilising the proposed controller design.

Abstract: This paper reports on the development and implementation of an algorithm for the design of spatially distributed feedback controllers for the wide variety of physical processes that are included in cross-directional (CD) control of industrial paper machines. The spatial and temporal structure of this class of process models is exploited in the use of the 2D frequency domain for analysis and 2D loop shaping design of feedback controllers. This algorithm forms the basis of a software tool that has recently been implemented in a commercial product and its use is illustrated for tuning CD controllers on two different industrial paper machines. The first example describes the use of the tool in stabilizing an unstable closed-loop system by retuning the distributed controller. The second paper machine example exposes an underperforming controller. Subsequent retuning of the controller resulted in a dramatic performance improvement.

Abstract: A method and system for power management including device controller-based device use evaluation and power-state control provides improved performance in a power-managed processing system. Per-device usage information is measured and evaluated during process execution and is retrieved from the device controller upon a context switch, so that upon reactivation of the process, the previous usage evaluation state can be restored. The device controller can then provide for per-process control of attached device power management states without intervention by the processor and without losing the historical evaluation state when a process is switched out. The device controller can control power-saving states of connected devices in conformity with the usage evaluation without processor intervention and across multiple process execution slices. The device controller may be a memory controller and the controlled devices memory modules or banks within modules if individual banks can be power-managed. Local thresholds provide the decision-making mechanism for each controlled device. The thresholds may be history-based, fixed or adaptive and are generally set initially by the operating system and may be updated by the memory controller adaptively or using historical collected usage evaluation counts or alternatively by the operating system via a system processor.

Abstract: In this paper, we investigate the output voltage control for three phase uninterruptible power supply (UPS) using controllers based on ideas of dissipativity. To provide balanced sinusoidal output voltages even in the presence of nonlinear and unbalanced loads, we first derive a dissipativity-based controller using a conventional /spl alpha//spl beta/ (fixed frame) representation of system dynamics and a frequency-domain representation of system disturbances. Adaptive refinements have been added to the controller to cope with parametric uncertainties. Second, based on the structure of the first adaptive controller, we propose another controller that leads to a linear time-invariant (LTI) closed loop system which is directly connected to synchronous frame harmonic voltage control. This controller, denoted as robust, avoids the most computationally demanding parameter estimation during adaptation, and offers important advantages for implementation. For the proposed robust controller, a sufficient condition in terms of the design parameters is presented to guarantee stability of the desired equilibrium and robustness against certain parametric uncertainties. Finally, simulation and experimental results on a three-phase prototype show effectiveness and advantages of the proposed class of controllers.

Abstract: Addresses model-based fuzzy control. A constructive and automated method for the design of a gain-scheduling controller is presented. Based on a given Takagi-Sugeno fuzzy model of the plant, the controller is designed such that stability and prescribed performance of the closed loop are guaranteed. These properties are valid in a wide working range around an equilibrium without restrictions to slowly varying trajectories. The synthesis is based on linear matrix inequalities and convex optimization techniques. If required, a fuzzy state estimator and an extended controller can be included, providing a zero steady-state error in the presence of disturbances and modeling errors. The proposed method has been applied to a control of a laboratory liquid-level process. Hence, the performance has been evaluated in simulations as well as in real-time control.

Abstract: In this paper, a novel neural network (NN) backstepping controller is modified for application to an industrial motor drive system. A control system structure and NN tuning algorithms are presented that are shown to guarantee stability and performance of the closed-loop system. The NN backstepping controller is implemented on an actual motor drive system using a two-PC control system developed at The University of Texas at Arlington. The implementation results show that the NN backstepping controller is highly effective in controlling the industrial motor drive system. It is also shown that the NN controller gives better results on actual systems than a standard backstepping controller developed assuming full knowledge of the dynamics. Moreover, the NN controller does not require the linear-in-the-parameters assumption or the computation of regression matrices required by standard backstepping.

Abstract: In this paper, we introduce a hexapedal locomotion controller that simulation evidence suggests will be capable of driving our RHex robot at speeds exceeding five body lengths per second with reliable stability and rapid maneuverability. We use a low dimensional passively compliant biped as a "template" - a control target for the alternating tripod gait of the physical machine. We impose upon the physical machine an approximate inverse dynamics within-stride controller designed to force the true high dimensional system dynamics down onto the lower dimensional subspace corresponding to the template. Numerical simulations suggest the presence of asymptotically stable running gaits with large basins of attraction. Moreover, this controller improves substantially the maneuverability and dynamic range of RHex's running behaviors relative to the initial prototype open-loop algorithms.

Abstract: This paper demonstrates the enhancement of inter-area mode damping by multiple flexible AC transmission systems (FACTS) devices. Power system damping control design is formulated as an output disturbance rejection problem. A decentralized H/sub /spl infin//, damping control design based on the mixed-sensitivity formulation in the linear matrix inequality (LMI) framework is carried out. A systematic procedure for selecting the weights for shaping the open loop plant for control design is suggested. A 16-machine, 5-area study system reinforced with a controllable series capacitor (CSC), a static VAr compensator (SVC) and a controllable phase shifter (CPS) at different locations is considered. The controllers designed for these devices are found to effectively damp out inter-area oscillations. The damping performance of the controllers is examined in the frequency and time domains for various operating scenarios. The controllers are found to be robust in the face of varying power-flow patterns, nature of loads, tie-line strengths and system nonlinearities, including device saturations.

Abstract: Introduces the auto disturbance rejection controller and its application on a Fast Following Synchronizer of Generator The numerical simulation shows that the controller ensures very good robustness under modeling uncertainty,and it is concluded that the proposed controller produces better dynamic performance such as small overshoot than the classic PID controller

Abstract: This paper presents a novel architecture for a unit-delay digital deadbeat current controller for a shunt active power filter (APF). The APF is based on a fixed frequency pulsewidth modulated voltage-sourced converter (VSC). The proposed controller increases the APF current-tracking bandwidth without increasing the VSC switching frequency. Previous APF digital deadbeat controllers have a current-tracking delay of two or more sample-periods. One delay is due to current controller computation, a second sample delay represents VSC actuation time. The paper presents a new controller architecture employing both asynchronous programmable logic and a small microprocessor. Current-tracking feedback control calculations are executed in asynchronous programmable logic to effectively eliminate the controller computation delay. The microprocessor executes fundamental frequency disturbance rejection computations and all other supervisory functions. The proposed architecture retains all high-level functions in the microprocessor to minimize controller development time without compromising APF performance.

Abstract: This brief presents an output feedback controller design method for piecewise discrete-time linear systems based on a piecewise Lyapunov function and a state observer. It is shown that the resulting closed-loop system is globally stable and the controller can be obtained by solving a set of linear matrix inequalities that is numerically feasible with commercially available software. In other words, it is shown that the separation principle of the controller and observer design is still maintained when the piecewise Lyapunov function is used. A simulation example is also given to illustrate the advantage of the proposed approach.

Abstract: We examine the complex problem of simultaneous position and internal force control in multiple cooperative manipulator systems. This is done in the presence of unwanted parametric and modeling uncertainties as well as external disturbances. A decentralized adaptive fuzzy controller scheme is proposed here. The controller makes use of a multi-input-multi-output fuzzy logic engine and a systematic online adaptation mechanism. Unlike conventional adaptive controllers, the proposed algorithm requires neither a precise mathematical model of the system's dynamics nor a linear parameterization of the system's uncertain physical parameters. Using a Lyapunov stability approach, the controller is proven to be robust in the face of varying intensity levels of the aforementioned uncertainties. The payload position/orientation error and that of the internal forces are also shown to asymptotically converge to zero under such conditions. The performance of the controller proposed is then compared with that of a well-known conventional adaptive controller.

Abstract: A method of using a run-to-run (R2R) controller to provide wafer-to-wafer (W2W) control in a semiconductor processing system is provided. The R2R controller includes a feed-forward (FF) controller, a process model controller, a feedback (FB) controller, and a process controller. The R2R controller uses feed-forward data, modeling data, feedback data, and process data to update a process recipe on a wafer-to-wafer time frame.

Abstract: This paper proposes a novel stepper motor controller based on field programable gate arrays, showing a remarkable performance. The system provides a combination between a novel algorithm and programmable logic to achieve both high speed and high precision on a compact hardware.

Abstract: In this paper, a simple method for the calculation of stabilizing PI controllers is given. The proposed method is based on plotting the stability boundary locus in the (k/sub p/, k/sub i/)-plane and then computing stabilizing values of the parameters of a PI controller. The technique presented does not require sweeping over the parameters and also does not need linear programming to solve a set of inequalities. Thus is offers several important advantages over existing results obtained in this direction. Beyond stabilization, the method is used to shift all poles to a shifted half plane that guarantees a specified settling time of response. Furthermore, computation of stabilizing PI controllers, which achieve user specified gain and phase margins is studied. It is also shown via an example that the stabilizing region in the (k/sub p/, k/sub i/)-plane is not always a convex set. The proposed method is also used to design PID controllers. The limiting values of the PID controller, which stabilize a given system are obtained in the (k/sub p/, k/sub d/)-plane and (k/sub i/, k/sub d/)-plane. Examples are given to show the benefit of the method presented.

Abstract: This paper describes a digital controller chip set for high-frequency DC-DC power converters with galvanic isolation. The secondary-side controller includes an A/D converter and a transmitter that sends a digital error signal as serial data through an opto-coupler. The primary-side controller includes a serial-data receiver, a programmable digital PID regulator, and a high-resolution (10-bit) digital pulse-width modulator. The digital error signal transmission through the isolation boundary eliminates the problem of gain variation when the opto-coupler is used in linear mode. The chip set is tested as a replacement for a conventional analog current-mode controller in a 3.3 V, 20 A, 400 KHz DC power supply. Experimental results with the digital controller show improved dynamic responses compared to the responses obtained with the analog controller.

Abstract: A refrigeration system including a compressor, condenser, valve, and evaporator in fluid communication; a system controller operable to control one or more aspects of the refrigeration system, and a subsystem controller in communication with the system controller. The subsystem controller is operable to control one of the compressor, condenser, valve, and evaporator. A method of operating the refrigeration system includes communicating a code from the subsystem controller to the system controller, obtaining information at the system controller having a relation to the code; and communicating at least a portion of the obtained information from the system controller to the subsystem controller.

Abstract: A theoretical and experimental comparison between standard and recently-developed improved indirect field-oriented controllers for induction motors is presented It is shown that standard indirect field-oriented control algorithm provides asymptotic speed and flux regulation, while the improved one guarantees global exponential speed-flux tracking under condition of constant load torque The difference between the flux sub-system design for the two controllers is analyzed It is shown that the improved controller provides closed loop properties for flux subsystem when motor is rotating, leading to robust stabilization of the rotor flux vector space position and robust tracking of its modulus It is demonstrated that both controllers have similar complexity and can be tuned using standard procedure for cascaded systems Intensive experimental study shows that improved controller provides about one order higher speed tracking performance as compared with standard solution Moreover, improved robustness with respect to rotor parameters variation leads to improved energy efficiency and robust stabilization of dynamic performance

Abstract: In this paper, we design an intelligent and robust stable fuzzy proportional-derivative (PD) controller for lateral control of passenger cars. An additional lateral displacement sensor is added at the tail bumper instead of gyro sensor in order to measure the yaw rate. First, a genetic-algorithm (GA)-based fuzzy PD controller is proposed to combine heuristics and optimization. Then, the fuzzy control system is transformed into a Lur'e system with uncertainties. The Lyapunov's direct method is used to guarantee the stability of the perturbed Lur'e system, and then a robustness measurement that gives the bound of the uncertainties is derived. The performance of the proposed controller is compared with a conventional PD controller through simulation studies. Experimental studies on a small-scale vehicle are also reported.