A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

Robust Quasi-LPV Controller Design via Integral Quadratic Constraint Analysis

Reduced cost of sensors and increased computing power is enabling the development and implementation of control systems that can simultaneously regulate multiple variables and handle conflicting objectives while maintaining stringent performance objectives. To make this a reality, practical analysis and design tools must be developed that allow the designer to trade-off conflicting objectives and guarantee performance in the presence of uncertain system dynamics, an uncertain environment, and over a wide range of operating conditions. As a first step towards this goal, we organize and streamline a promising robust control approach, Robust Linear Parameter Varying control, which integrates three fields of control theory: Integral Quadratic Constraints (IQC) to characterize uncertainty and nonlinearities, Linear Parameter Varying systems (LPV) that formalizes gain-scheduling, and convex optimization to solve the resulting robust control Linear Matrix Inequalities (LMI). To demonstrate the potential of this approach, it was applied to the design of a robust linear parametrically varying controller for an ecosystem with nonlinear predator-prey-hunter dynamics

Passivity-Based adaptive bilateral teleoperation control for uncertain manipulators without jerk measurements

In this work, we consider the bilateral teleoperation problem of cooperative robotic systems in a Single-Master Multi-Slave (SM/MS) configuration, which is able to perform load transportation tasks in the presence of parametric uncertainty in the robot kinematic and dynamic models. The teleoperation architecture is based on the two-layer approach placed in a hierarchical structure, whose top and bottom layers are responsible for ensuring the transparency and stability properties respectively. The load transportation problem is tackled by using the formation control approach wherein the desired translational velocity and interaction force are provided to the master robot by the user, while the object is manipulated with a bounded constant force by the slave robots. Firstly, we develop an adaptive kinematic-based control scheme based on a composite adaptation law to solve the cooperative control problem for robots with uncertain kinematics. Secondly, the dynamic adaptive control for cooperative robots is implemented by means of a cascade control strategy, which does not require the measurement of the time derivative of force (which requires jerk measurements). The combination of the Lyapunov stability theory and the passivity formalism are used to establish the stability and convergence property of the closed-loop control system. Simulations and experimental results illustrate the performance and feasibility of the proposed control scheme.No presente trabalho, considera-se o problema de teleoperação bilateral de um sistema robótico cooperativo do tipo single-master e multiple-slaves (SM/MS) capaz de realizar tarefas de transporte de carga na presença de incertezas paramétricas no modelo cinemático e dinâmico dos robôs. A arquitetura de teleoperação está baseada na abordagem de duas camadas em estrutura hierárquica, onde as camadas superior e inferior são responsáveis por assegurar as propriedades de transparência e estabilidade respectivamente. O problema de transporte de carga é formulado usando a abordagem de controle de formação onde a velocidade de translação desejada e a força de interação são fornecidas ao robô mestre pelo operador, enquanto o objeto é manipulado pelos robôs escravos com uma força constante limitada. Primeiramente, desenvolve-se um esquema de controle adaptativo cinemático baseado em uma lei de adaptação composta para solucionar o problema de controle cooperativo de robôs com cinemática incerta. Em seguida, o controle adaptativo dinâmico de robôs cooperativos é implementado por meio de uma estratégia de controle em cascata, que não requer a medição da derivada da força (o qual requer a derivada da aceleração ou jerk). A teoria de estabilidade de Lyapunov e o formalismo de passividade são usados para estabelecer as propriedades de estabilidade e a convergência do sistema de controle em malha-fechada. Resultados de simulações numéricas ilustram o desempenho e viabilidade da estratégia de controle proposta

Model-Based Cyber-Security Framework for Nuclear Power Plant

A model-based cyber-security framework has been developed to address the new challenges of cyber threats due to the increasing implementation of digital components in the instrumentation and control (I&C) system of modern nuclear power plants. The framework is developed to detect intrusions to pressurized water reactor (PWR) systems that could result in unnecessary reactor shutdown events due to out-of-range water levels of steam generators. The generation of potential attack scenarios demonstrated a process for identifying the most susceptible attack pathways and components in the I&C system. It starts with identifying two key I&C divisions of the modern AP1000 design related to the reactor trip functions, protection and safety monitoring system, and plant control system. The attack tree analysis is performed on the steam generator (SG) water level control system using the SAPHIRE 8.0.9 code. To quantify the system susceptibility to cyber-attack events, causing reactor trips, we propose sensitivity metrics to identify the low-order sets of components that may be compromised and the degree of perturbations needed for each component. The multi-path event tree (MPET) structures are developed to efficiently and intuitively display a large number of dominant or risk-significant attack scenarios instead of the traditional event trees representing minimal cut sets. A reduced order model (ROM) has been developed to efficiently represent the SG dynamics and facilitate the detection of potential cyber-attacks. The dynamic ROM is built on the energy balance equation for a single vertical boiling channel approximating a U-tube steam generator. The ROM provides an essential relationship connecting the reactor power, water level, and feedwater flow rate. An application programming interface (API) for the I&C systems serving as the interface between the RELAP5 system code and the ROM has been developed. A Kalman filtering based detection method has been proposed, providing optimal tracking of SG water level combining the uncertain simulation results with the observation data subject to statistical fluctuations. An observed plant state with significant deviation from the optimal system projection could then indicate potential intrusions into the system. Finally, a mitigation strategy considering the controller feedback is proposed to avoid the reactor trip due to attack on SG water level sensors. The worst-case attack within this issue space is defined, and the maximum delay time allowed for the mitigation is obtained.PHDNuclear Engineering & Radiological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162955/1/gjunjie_1.pd

Intelligent flight control systems

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms