·       Adaptive Inverse Control of Systems with Practical Nonsmooth Nonlinearities

(An NSF research initiation award - the NSF grant ECS-9307545)

Project Summary

This proposal describes a project to explore a new area of adaptive control and to address open problems of urgent relevance to theory as well as applications: adaptive control of systems consisting of a linear part and a nonsmooth nonlinear input-output characteristic being in either an actuator or a sensor. Typical examples of such nonlinear characteristics are dead-zone, backlash and hysteresis. An adaptive inverse approach is proposed to control such systems to meet desired performance specifications, which exploits an adaptive inverse for an unknown nonlinearity and a linear controller structure nonadaptive/adaptive for a known/unknown linear part. Choices of nonlinear models, design of adaptive inverse control algorithms, stability, convergence and robustness analysis, and applications will be investigated. The results of this research will provide new tools to handle unknown nonsmooth nonlinearities which are common in practical control systems.

·       Adaptive Control of Sandwich Nonlinear Systems with Applications

(An NSF GOALI (Grants Opportunities for Academic Liaison with Industry) award - the NSF grant ECS-9619363)

Project Summary

This proposal describes a university-industry collaborative research project to explore a new area of adaptive control: adaptive control of sandwich nonlinear systems , and to solve some long-standing and wide-range control problems of urgent relevance to theory as well as applications. The proposed research will focus on adaptive control of sandwich systems with linear and nonsmooth nonlinear dynamics and on adaptive control of two-layer systems with smooth and nonsmooth nonlinear dynamics. Typical nonsmooth nonlinear characteristics are dead-zone, backlash, hysteresis, other piecewise-linearities as well as frictions which are the main sources of component imperfections in control systems. The proposed adaptive inverse control approach employs an adaptive inverse to cancel the nonlinearity effects in order to achieve system performance improvements. This approach points to a new direction to design control systems using a new algorithm-based technology, which, after a period of learning or adaptation, can recognize component imperfections and compensate for their harmful effects. With such adaptive controllers, the component specifications could be greatly relaxed, their cost reduced, and their reliability increased. The results of this research will advance the knowledge of adaptive control significantly, provide new tools to effectively handle practical nonlinearities which have haunted the constructors of control systems for many years, and have many applications in defense and civil industries in which high-precision control systems are vital components.

·       Adaptive Failure Compensation for Performance-Critical Control Systems

(A research project supported by the NSF grant ECS-0601475, 06/2006 - 05/2010)

Project Summary

This proposal describes a research project to develop new adaptive failure compensation techniques for dynamic systems with uncertain failures. The proposed research is focused on the development of a novel systematic theoretical framework for adaptive failure compensation and specific solutions for several synergic topics, to provide guidelines for designing control systems with guaranteed stability and tracking performance in the presence of system parameter, dynamics and failure uncertainties, with applications to performance-critical control systems. New theories of nonlinear and multivariable adaptive control, new approaches for system modeling in the presence of system failures, and new methods of adaptive failure compensation will be explored for new advances in this open area of research.

The first topic is the development of novel system modeling and adaptive control approaches for systems with failures. For many applications, models of systems with failure and without failures are essentially different (for example, aircraft flight dynamics in an engine differential mode). We will develop novel system models which capture the key features of dynamic systems in the presence of failures, based which effective failure compensation schemes can be designed. The second topic is the development of adaptive failure compensation schemes for multivariable systems with space structure vibration reduction control applications. The third topic is adaptive compensation of failures in cooperating multiple manipulator systems. New controller parametrization and adaptive laws are needed for intelligent autonomous robot control systems which can adaptively compensate for uncertain failures. The fourth topic is control of systems with MEM devices as actuators which may fail during system operation. Effective compensation of failures of MEM devices is a key component of successful MEMS technology and this research is to develop such techniques illustrated by control of morphing actuators and synthetic jet actuators applied to aircraft flight control. The unified theme of these topics is failure compensation by direct adaptation of controller parameters without explicit fault detection and diagnosis, aimed at achieving fast response and effective compensation of uncertain failures. The unique feature of adaptive failure compensation is that it ensures both stability and asymptotic tracking, without the knowledge of when, how much and how many failures appearing in the system. The importance of this research is its potential for significantly improving control system performance in the presence of uncertain failures for performance-critical applications.

Intellectual merit: The proposed activities has high intellectual merit. Adaptive failure compensation has open issues such as failure induced parameter/structure uncertainties, system failure compensability, controller adaptivity to uncertain failures, system stabilizability under multiple failure patterns, and advanced applications, which are both important and challenging in theory and practice as well. Those issues contribute to the unique features of the control problems investigated in the project, and their solutions will lead to creative concepts and effective methods for fields of systems and control. This research will develop novel solutions to such issues, which will advance the state-of-the-art in adaptive control theory and emerging applications such as MEM technology, safe aircraft and intelligent robot systems. Preliminary study has shown encouraging results of this promising adaptive compensation approach.

Broader impacts: This research will have major impact on technology as it will develop novel system modeling and adaptive control techniques for aircraft flight systems, intelligent robot systems, active vibration control systems, and for control of systems with MEM devices such as morphing actuators and synthetic jet actuators, with uncertainty adaptation and failure compensation capacities to improve system reliability, maintainability and survivability. Impact on education will be strong as the research activities and results will bring new concepts and theory of adaptive control into student training and knowledge dissemination. Impact on outreach will be broad as the proposed adaptive failure compensation techniques have attracted academic and industrial/government researchers such as NASA and Air Force.

·       Adaptive Fault Accommodation Based Resilient Control Techniques

(A research project supported by the NSF grant ECCS-1509704, 08/2015 - 07/2018)

Project Summary

This research project is to solve open control theoretical problems to build technical foundations for designing resilient control systems which are capable of maintaining desired performance in the presence of uncertain system faults such as actuator failures, structural damage and sensor failures. This research is aimed at developing new fault detection algorithms and new adaptive and robust control methods and criteria to handle large and multiple system fault uncertainties. It will create new resilient control theory and techniques applicable to performance-critical systems such as aircraft, spacecraft, wind turbines, jet engines and intelligent robots, to enhance their safety under uncertain fault conditions. It will conduct new studies on modeling and control of systems under various fault conditions for which existing control designs are not applicable. For example, aircraft loss-of-control precursor conditions such as airframe damage, component failures, icing and turbulence effects may cause large and variant system uncertainties for which existing feedback controllers are not powerful enough. The research is expected to advance feedback control theory and technology for the need of emerging applications which require control systems to be resilient to faults, that is, have desired capabilities to accommodate uncertain and large system faults.

This research studies unique metrics of control system resilience, distinct features of resilient control problems, and key control theory requirements of performance-critical systems. It develops new control theory and design techniques to ensure desired control system resilience for multivariable nonlinear systems under uncertain multi-fault conditions. It solves new control problems such as fault detection for unstable systems, control of systems with uncertain structural characterizations or non-parametrizable non-canonical form nonlinear dynamics, adaptive and fault-tolerant control of systems with underactuation or nonminimum phase. These problems have the key feature that the controlled systems have fault-induced parametric, structural and functional uncertainties, difficult for most existing control schemes to deal with (to ensure both system stability and asymptotic tracking). For example, there can be uncertain failure patterns, uncertain underactuation, uncertain system infinite zero structures, uncertain dynamic variations, caused by uncertain faults.

A main goal of this research is to build a new control system design framework with specific control schemes which are capable of dealing with such unsolved system uncertainty problems, needed for resilient control systems technology. Several new feedback control methods will be developed, including: adaptive multi-layer multiple-model design (to ensure both fault handling and performance improvement abilities), adaptive multi-design integration (to deal with multiple faults), adaptive feedback-based fault detection (to have self-stabilization capacity), adaptive structural uncertainty accommodation (to deal large system structural damage), and characteristic parametrization based adaptive approximation control for non-canonical form nonlinear systems (to design an adaptable and stable controller structure). Direct control adaptation techniques will be developed for fast and smooth compensation of large and multiple fault uncertainties. New resilient control designs, for performance-guarantee fault-tolerant control, will be tested on some benchmark application system models. New concepts, theory and techniques for resilient control systems will be used for student training and knowledge dissemination.

Novel outcomes expected from this research include: a new resilient control theoretical framework with new solutions to some key technical problems; a new direct adaptive multi-layer multiple-model control method for uncertain MIMO systems; a new adaptive feedback-based fault detection scheme with guaranteed stable detection conditions; a new adaptive multi-design integration based method for multi-fault accommodation; new fault detection and fault-tolerant control designs for aircraft, wind turbine, jet engine and robot system models; and scalable fault accommodation designs applicable to multiple (combined and sequentially or recurrently occurred) uncertain faults.