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In this paper, a learning-based feedforward term is developed to solve a general control problem in the presence of unknown nonlinear dynamics with a known period. Since the learning-based feedforward term is generated from a straightforward Lyapunov-like stability analysis, the control designer can utilize other Lyapunov-based design techniques to develop hybrid control schemes that utilize learning-based feedforward terms to compensate for periodic dynamics and other Lyapunov-based approaches (e.g., adaptive-based feedforward terms) to compensate for non-periodic dynamics. To illustrate this point, a hybrid adaptive/learning control scheme is utilized to achieve global asymptotic link position tracking for a robot manipulator.

This paper seeks to begin a discussion with regard to developing computer aided control system design (CACSD) tools to promote undergraduate controls laboratory development. The advocated CACSD design tools are based on the popular, commercially available MATLAB environment, the Simulink toolbox, and the Real-Time Workshop toolbox. This paper describes how these tools can be utilized to address several issues that are confronted by control systems educators including: standardization, budget constraints, and limited resources. Specifically, by confronting the standardization issue, the following advantages are realized for laboratory development: (1) the required computer hardware will be low cost; (2) commercially available plants from different manufacturers can be supported under the same CACSD environment with no hardware modifications; (3) both the Windows and Linux operating systems can be supported via the MATLAB based Real-Time Windows Target and the Quality Real-Time Systems (QRTS) based Real-Time Linux Target; and (4) the Simulink block diagram approach can be utilized to prototype control strategies, thereby, eliminating the need for low level programming skills. The advantages related to standardization of the CACSD design tools will enable educators to confront the additional budget constraint and limited teaching resources issue by facilitating: (1) the sharing of laboratory resources within each university (i.e., between departments); (2) the development of Internet laboratory experiences for students (i.e., between universities); and (3) the initiation of an Internet-based archive of laboratory tutorials and Simulink files for in-house developed plants and commercially available plants.

We design a control strategy for a rotating unbalanced disk. The control strategy is composed of a control torque and two control forces. The control strategy regulates disk displacement while ensuring that the unbalanced disk tracks a desired angular velocity trajectory. Specifically the control uses a desired compensation adaptation law (DCAL) and a gain adjusted forgetting factor to achieve exponential stability despite the lack of knowledge of the imbalance-related parameters provided a mild persistency of excitation condition is satisfied.

In this paper, we present the design of boundary controllers for a two-dimensional, spinning flexible rotor system. Specifically, we develop a model-based boundary controller which exponentially regulates the rotor's displacement and the angular velocity tracking error, and an adaptive boundary controller which asymptotically achieves the same control objective while compensating for parametric uncertainty. As opposed to previous boundary control work, which focused on the velocity setpoint problem and placed restrictions on the magnitude of the desired angular velocity setpoint, the proposed control architecture achieves angular velocity tracking with no restrictions on the magnitude of the desired velocity trajectory. Experimental results conducted on a flexible rotor tested are presented to illustrate the feasibility of implementing the proposed boundary control laws. Copyright © 2001 John Wiley & Sons, Ltd.

This paper is devoted to the use of multiple flywheels that integrate the energy storage and attitude control functions in space vehicles. This concept, which we refer to as an integrated energy management and attitude control (IEMAC) system, reduces the space vehicle bus mass, volume, cost, and maintenance requirements while maintaining or improving the space vehicle performance. To this end, we present two nonlinear IEMAC strategies (model-based and adaptive) that simultaneously track a desired attitude trajectory and desired energy/power profile. Both strategies ensure asymptotic tracking while the adaptive controller compensates for uncertain spacecraft inertia.

We present a control strategy for an axially moving string system that achieves vibration regulation along the string and ensures that the string tracks a desired axial velocity trajectory. The control strategy is implemented by utilizing the roller torque inputs applied at the entry and exit points of the string and a pair of control forces applied to the string via an interstitial mechanical guide. Given the hybrid model of the string system (i.e., the distributed parameter field equation coupled to discrete actuator equations), Lyapunov-type arguments are utilized to design a model-based control law that exponentially regulates the axial velocity tracking error and the string displacement along the entire span. The proposed control law is based on measurements of the string displacement, velocity, slope, and slope rate at the mechanical guide.

In this paper, we present the design of boundary controllers for a two-dimensional, spinning flexible rotor system. Specifically, we develop a model-based boundary controller which exponentially regulates the rotor's displacement and the angular velocity tracking error, and an adaptive boundary controller which asymptotically achieves the same control objective while compensating for parametric uncertainty. As opposed to previous boundary control work, which focused on the velocity setpoint problem and placed restrictions on the magnitude of the desired angular velocity setpoint, the proposed control architecture achieves angular velocity tracking with no restrictions on the magnitude of the desired velocity trajectory.

The main problem addressed in this paper is the quaternion-based, attitude tracking control of rigid spacecraft without angular velocity measurements and in the presence of an unknown inertia matrix. As a stepping-stone, we first design an adaptive, full-state feedback controller that compensates for parametric uncertainty while ensuring asymptotic attitude tracking errors. The adaptive, full-state feedback controller is then re-designed such that the need for angular velocity measurements is eliminated. The proposed adaptive, output feedback controller ensures asymptotic attitude tracking.

The paper seeks to begin a discussion with regard to developing standardized computer aided control system design (CACSD) tools that are typically utilized in an undergraduate controls laboratory. The advocated CACSD design tools are based on the popular, commercially available MATLAB environment, the Simulink toolbox, and the Real-Time Workshop toolbox. The primary advantages of the proposed approach are as follows: 1) the required computer hardware is low cost, 2) commercially available plants from different manufacturers can be supported under the same CACSD environment with no hardware modifications, 3) both the Windows and Linux operating systems can be supported via the MATLAB based Real-Time Windows Target and the Quality Real Time Systems (QRTS) based Real-Time Linux Target, and 4) the Simulink block diagram approach can be utilized to prototype control strategies; thereby, eliminating the need for low level programming skills. It is believed that the above advantages related to standardization of the CACSD design tools will facilitate: 1) the sharing of laboratory resources within each university (i.e., between departments) and 2) the development of Internet laboratory experiences for students (i.e., between universities).

We present a modular control strategy to achieve global asymptotic stability for the regulation problem of a single-axis active magnetic bearing (AMB) in the presence of an unknown sinusoidal disturbance (i.e., the amplitude and the frequency are unknown). Specifically, we design a set of linear, BIBO filters to facilitate the utilization of standard adaptive control techniques to compensate for the effects of the unknown sinusoidal disturbance. In view of the fact that the disturbance frequency might slowly vary with time, we utilize a least squares prediction error-based update law to promote faster convergence of the parameter estimates.

This paper presents a nonlinear control method for the active magnetic bearing benchmark system. A flux input controller, based on a new iterative learning control strategy, is proposed to asymptotically regulate the system while compensating for periodic, exogenous disturbances. Numerical simulation results are presented to illustrate the performance of the proposed controller.

We design a control strategy for a spinning rotor with an unbalanced disk attached to its free end. The control strategy is composed of a boundary torque applied to the clamped end, and two boundary forces and two boundary torques applied to the free-end. At the clamped-end, the boundary torque ensures that the rotor tracks a desired angular velocity trajectory, while at the free-end, the boundary forces and torques ensure that the rotor displacement is regulated at every point along the length of the rotor. Under the assumption of exact model knowledge, we first develop a model-based control law which exponentially achieves the control objectives. We then illustrate how the model-based control law can be redesigned as an adaptive controller which asymptotically achieves the same control objectives while compensating for parametric uncertainty associated with unbalanced operation.

We study the control of an undamped, nonlinear string model with actuator dynamics at the boundary. Specifically, we develop a boundary controller which asymptotically stabilizes the out-of-plane displacement. The performance of the controller is illustrated via dynamic simulation.