Nonlinear and adaptive control

The primary thrust of the research was to conduct fundamental research in the theories and methodologies for designing complex high-performance multivariable feedback control systems; and to conduct feasibiltiy studies in application areas of interest to NASA sponsors that point out advantages and shortcomings of available control system design methodologies

Vibration suppression in multi-body systems by means of disturbance filter design methods

This paper addresses the problem of interaction in mechanical multi-body systems and shows that subsystem interaction can be considerably minimized while increasing performance if an efficient disturbance model is used. In order to illustrate the advantage of the proposed intelligent disturbance filter, two linear model based techniques are considered: IMC and the model based predictive (MPC) approach. As an illustrative example, multivariable mass-spring-damper and quarter car systems are presented. An adaptation mechanism is introduced to account for linear parameter varying LPV conditions. In this paper we show that, even if the IMC control strategy was not designed for MIMO systems, if a proper filter is used, IMC can successfully deal with disturbance rejection in a multivariable system, and the results obtained are comparable with those obtained by a MIMO predictive control approach. The results suggest that both methods perform equally well, with similar numerical complexity and implementation effort

Modeling and supervisory control design for a combined cycle power plant

The traditional control strategy based on PID controllers may be unsatisfactory when dealing with processes with large time delay and constraints. This paper presents a supervisory model based constrained predictive controller (MPC) for a combined cycle power plant (CCPP). First, a non-linear dynamic model of CCPP using the laws of physics was proposed. Then, the supervisory control using the linear constrained MPC method was designed to tune the performance of the PID controllers by including output constraints and manipulating the set points. This scheme showed excellent tracking and disturbance rejection results and improved performance compared with a stand-alone PID controller’s scheme

The application of a new PID autotuning method for the steam/water loop in large scale ships

In large scale ships, the most used controllers for the steam/water loop are still the proportional-integral-derivative (PID) controllers. However, the tuning rules for the PID parameters are based on empirical knowledge and the performance for the loops is not satisfying. In order to improve the control performance of the steam/water loop, the application of a recently developed PID autotuning method is studied. Firstly, a 'forbidden region' on the Nyquist plane can be obtained based on user-defined performance requirements such as robustness or gain margin and phase margin. Secondly, the dynamic of the system can be obtained with a sine test around the operation point. Finally, the PID controller's parameters can be obtained by locating the frequency response of the controlled system at the edge of the 'forbidden region'. To verify the effectiveness of the new PID autotuning method, comparisons are presented with other PID autotuning methods, as well as the model predictive control. The results show the superiority of the new PID autotuning method

Additive-Decomposition-Based Output Feedback Tracking Control for Systems with Measurable Nonlinearities and Unknown Disturbances

In this paper, a new control scheme, called as additive-decomposition-based tracking control, is proposed to solve the output feedback tracking problem for a class of systems with measurable nonlinearities and unknown disturbances. By the additive decomposition, the output feedback tracking task for the considered nonlinear system is decomposed into three independent subtasks: a pure tracking subtask for a linear time invariant (LTI) system, a pure rejection subtask for another LTI system and a stabilization subtask for a nonlinear system. By benefiting from the decomposition, the proposed additive-decomposition-based tracking control scheme i) can give a potential way to avoid conflict among tracking performance, rejection performance and robustness, and ii) can mix both design in time domain and frequency domain for one controller design. To demonstrate the effectiveness, the output feedback tracking problem for a single-link robot arm subject to a sinusoidal or a general disturbance is solved respectively, where the transfer function method for tracking and rejection and backstepping method for stabilization are applied together to the design.Comment: 23 pages, 6 figure

Multivariable Inferential Feed-Forward Control

Two multivariable inferential feed-forward control strategies are proposed in this paper. In the first strategy, the effects of disturbances on the primary process variables are inferred from uncontrolled secondary process variables that are measured on-line. In the second approach, the effects of disturbances on the primary process variables are inferred from the manipulated variables for those controlled secondary process variables that have fast dynamics. The proposed strategies are particularly useful in situations where some disturbances cannot be easily and quickly measured. Robustness analysis of the inferential feed-forward controllers and the selection of appropriate secondary measurements are discussed. Structured singular value analysis is used in assessing the robustness of the inferential feed-forward control systems. The performance characteristics of the two inferential feed-forward control systems are demonstrated by application to a simulated methanol-water separation column. In the first system, the effects of disturbances in feed composition (and feed rate) are inferred from tray temperatures, whereas in the second system, the disturbance effects are inferred from inventory manipulations. Nonlinear dynamic simulation results demonstrate the superior performance of these strategies. Robustness analysis shows that using multiple tray temperatures can improve the robustness of the inferential feed-forward controller, and this conclusion is confirmed by simulation

Adaptive Neural Network Feedforward Control for Dynamically Substructured Systems

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Robust detection, isolation and accommodation for sensor failures

The objective is to extend the recent advances in robust control system design of multivariable systems to sensor failure detection, isolation, and accommodation (DIA), and estimator design. This effort provides analysis tools to quantify the trade-off between performance robustness and DIA sensitivity, which are to be used to achieve higher levels of performance robustness for given levels of DIA sensitivity. An innovations-based DIA scheme is used. Estimators, which depend upon a model of the process and process inputs and outputs, are used to generate these innovations. Thresholds used to determine failure detection are computed based on bounds on modeling errors, noise properties, and the class of failures. The applicability of the newly developed tools are demonstrated on a multivariable aircraft turbojet engine example. A new concept call the threshold selector was developed. It represents a significant and innovative tool for the analysis and synthesis of DiA algorithms. The estimators were made robust by introduction of an internal model and by frequency shaping. The internal mode provides asymptotically unbiased filter estimates.The incorporation of frequency shaping of the Linear Quadratic Gaussian cost functional modifies the estimator design to make it suitable for sensor failure DIA. The results are compared with previous studies which used thresholds that were selcted empirically. Comparison of these two techniques on a nonlinear dynamic engine simulation shows improved performance of the new method compared to previous technique

Robust and Decentralized Control of Web Winding Systems

This research addresses the velocity and tension regulation problems in web handling, including those found in the single element of an accumulator and those in the large-scale system settings. A continuous web winding system is a complex large-scale interconnected dynamics system with numerous tension zones to transport the web while processing it. A major challenge in controlling such systems is the unexpected disturbances that propagate through the system and affect both tension and velocity loops along the way. To solve this problem, a unique active disturbance rejection control (ADRC) strategy is proposed. Simulation results show remarkable disturbance rejection capability of the proposed control scheme in coping with large dynamic variations commonly seen in web winding systems. Another complication in web winding system stems from its large-scale and interconnected dynamics which makes control design difficult. This motivates the research in formulating a novel robust decentralized control strategy. The key idea in the proposed approach is that nonlinearities and interactions between adjunct subsystems are regarded as perturbations, to be estimated by an augmented state observer and rejected in the control loop, therefore making the local control design extremely simple. The proposed decentralized control strategy was implemented on a 3-tension-zone web winding processing line. Simulation results show that the proposed control method leads to much better tension and velocity regulation quality than the existing controller common in industry. Finally, this research tackles the challenging problem of stability analysis. Although ADRC has demonstrated the validity and advantage in many applications, the rigorous stability study has not been fully addressed previously. To this end, stability characterization of ADRC is carried out in this work. The closed-loop system is first reformulated, resulting in a form that allows the application of the well established singular perturbation method. Based on the decom