Global Stabilization of Triangular Systems with Time-Delayed Dynamic Input Perturbations

A control design approach is developed for a general class of uncertain strict-feedback-like nonlinear systems with dynamic uncertain input nonlinearities with time delays. The system structure considered in this paper includes a nominal uncertain strict-feedback-like subsystem, the input signal to which is generated by an uncertain nonlinear input unmodeled dynamics that is driven by the entire system state (including unmeasured state variables) and is also allowed to depend on time delayed versions of the system state variable and control input signals. The system also includes additive uncertain nonlinear functions, coupled nonlinear appended dynamics, and uncertain dynamic input nonlinearities with time-varying uncertain time delays. The proposed control design approach provides a globally stabilizing delay-independent robust adaptive output-feedback dynamic controller based on a dual dynamic high-gain scaling based structure.Comment: 2017 IEEE International Carpathian Control Conference (ICCC

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

Linear active disturbance rejection control of the hovercraft vessel model

A linearizing robust dynamic output feedback control scheme is proposed for earth coordinate position variables trajectory tracking tasks in a hovercraft vessel model. The controller design is carried out using only position and orientation measurements. A highly simplified model obtained from flatness considerations is proposed which vastly simplifies the controller design task. Only the order of integration of the input-to-flat output subsystems, along with the associated input matrix gain, is retained in the simplified model. All the unknown additive nonlinearities and exogenous perturbations are lumped into an absolutely bounded, unstructured, vector of time signals whose components may be locally on-line estimated by means of a high gain Generalized Proportional Integral (GPI) observer. GPI observers are the dual counterpart of GPI controllers providing accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and endogenous perturbation inputs. These observers exhibit remarkably convenient self-updating internal models of the unknown disturbance input vector components. These two key pieces of on-line information are used in the proposed feedback controller to conform an active disturbance rejection, or disturbance accommodation, control scheme. Simulation results validate the effectiveness of the proposed design method

Global Output Feedback Stabilization of a Class of Nonlinear Systems With Multiple Output

This paper considers global output feedback stabilization of a class of upper-triangular nonlinear systems with multiple outputs. By coupling a finite-time convergent observer and a saturated homogeneous stabilizer, the global output feedback stabilization can be achieved without the homogeneous growth condition. The proposed techniques are also extended to more general complex nonlinear systems. Various examples, including a ball-and-beam mechanical system and a planar vertical takeoff and landing aircraft, are presented to illustrate the design

Networked Control System Design and Parameter Estimation

Networked control systems (NCSs) are a kind of distributed control systems in which the data between control components are exchanged via communication networks. Because of the attractive advantages of NCSs such as reduced system wiring, low weight, and ease of system diagnosis and maintenance, the research on NCSs has received much attention in recent years. The first part (Chapter 2 - Chapter 4) of the thesis is devoted to designing new controllers for NCSs by incorporating the network-induced delays. The thesis also conducts research on filtering of multirate systems and identification of Hammerstein systems in the second part (Chapter 5 - Chapter 6). Network-induced delays exist in both sensor-to-controller (S-C) and controller-to-actuator (C-A) links. A novel two-mode-dependent control scheme is proposed, in which the to-be-designed controller depends on both S-C and C-A delays. The resulting closed-loop system is a special jump linear system. Then, the conditions for stochastic stability are obtained in terms of a set of linear matrix inequalities (LMIs) with nonconvex constraints, which can be efficiently solved by a sequential LMI optimization algorithm. Further, the control synthesis problem for the NCSs is considered. The definitions of H₂ and H∞ norms for the special system are first proposed. Also, the plant uncertainties are considered in the design. Finally, the robust mixed H₂/H∞ control problem is solved under the framework of LMIs. To compensate for both S-C and C-A delays modeled by Markov chains, the generalized predictive control method is modified to choose certain predicted future control signal as the current control effort on the actuator node, whenever the control signal is delayed. Further, stability criteria in terms of LMIs are provided to check the system stability. The proposed method is also tested on an experimental hydraulic position control system. Multirate systems exist in many practical applications where different sampling rates co-exist in the same system. The l₂-l∞ filtering problem for multirate systems is considered in the thesis. By using the lifting technique, the system is first transformed to a linear time-invariant one, and then the filter design is formulated as an optimization problem which can be solved by using LMI techniques. Hammerstein model consists of a static nonlinear block followed in series by a linear dynamic system, which can find many applications in different areas. New switching sequences to handle the two-segment nonlinearities are proposed in this thesis. This leads to less parameters to be estimated and thus reduces the computational cost. Further, a stochastic gradient algorithm based on the idea of replacing the unmeasurable terms with their estimates is developed to identify the Hammerstein model with two-segment nonlinearities. Finally, several open problems are listed as the future research directions

Robust Control Methods for Nonlinear Systems with Uncertain Dynamics and Unknown Control Direction

Robust nonlinear control design strategies using sliding mode control (SMC) and integral SMC (ISMC) are developed, which are capable of achieving reliable and accurate tracking control for systems containing dynamic uncertainty, unmodeled disturbances, and actuator anomalies that result in an unknown and time-varying control direction. In order to ease readability of this dissertation, detailed explanations of the relevant mathematical tools is provided, including stability denitions, Lyapunov-based stability analysis methods, SMC and ISMC fundamentals, and other basic nonlinear control tools. The contributions of the dissertation are three novel control algorithms for three different classes of nonlinear systems: single-input multipleoutput (SIMO) systems, systems with model uncertainty and bounded disturbances, and systems with unknown control direction. Control design for SIMO systems is challenging due to the fact that such systems have fewer actuators than degrees of freedom to control (i.e., they are underactuated systems). While traditional nonlinear control methods can be utilized to design controllers for certain classes of cascaded underactuated systems, more advanced methods are required to develop controllers for parallel systems, which are not in a cascade structure. A novel control technique is proposed in this dissertation, which is shown to achieve asymptotic tracking for dual parallel systems, where a single scalar control input directly affects two subsystems. The result is achieved through an innovative sequential control design algorithm, whereby one of the subsystems is indirectly stabilized via the desired state trajectory that is commanded to the other subsystem. The SIMO system under consideration does not contain uncertainty or disturbances. In dealing with systems containing uncertainty in the dynamic model, a particularly challenging situation occurs when uncertainty exists in the input-multiplicative gain matrix. Moreover, special consideration is required in control design for systems that also include unknown bounded disturbances. To cope with these challenges, a robust continuous controller is developed using an ISMC technique, which achieves asymptotic trajectory tracking for systems with unknown bounded disturbances, while simultaneously compensating for parametric uncertainty in the input gain matrix. The ISMC design is rigorously proven to achieve asymptotic trajectory tracking for a quadrotor system and a synthetic jet actuator (SJA)-based aircraft system. In the ISMC designs, it is assumed that the signs in the uncertain input-multiplicative gain matrix (i.e., the actuator control directions) are known. A much more challenging scenario is encountered in designing controllers for classes of systems, where the uncertainty in the input gain matrix is extreme enough to result in an a priori-unknown control direction. Such a scenario can result when dealing with highly inaccurate dynamic models, unmodeled parameter variations, actuator anomalies, unknown external or internal disturbances, and/or other adversarial operating conditions. To address this challenge, a SMCbased self-recongurable control algorithm is presented, which automatically adjusts for unknown control direction via periodic switching between sliding manifolds that ultimately forces the state to a converging manifold. Rigorous mathematical analyses are presented to prove the theoretical results, and simulation results are provided to demonstrate the effectiveness of the three proposed control algorithms

Diseño de un controlador de seguimiento para un sistema SISO de servoposicionamiento neumático

Pneumatic systems have many advantages, such as simplicity, reliability, low-cost, long life, etc. making them attractive for rapid development and widespread application, but the complexity of the airflow through the valve port and the friction between the cylinder and piston make it difficult to establish an exact mathematical model and control the pneumatic system with high precision. Experiments were conducted with a 25 mm bore rod-less pneumatic cylinder and a 5/3 way proportional control valve. In this contribution, I propose a nonlinear robust tracking control strategy to solve the tracking problem of the servo pneumatic positioning system. The approach is novel in the sense that it takes into account the nonlinearities inherent to pneumatic servo positioning systems and considers position, velocity and pressure difference in the chambers of the pneumatic cylinder as feedback states. The suggested control strategy is implemented in simulation and on the real system. Experimental results from an implementation on a test ring show a high position tracking control performance.Los sistemas neumáticos tienen varias ventajas que permitieron su rápido desarrollo y uso generalizado, tales como: simplicidad, confiabilidad, bajo costo, larga vida etc. Sin embargo, la complejidad del flujo de aire a través de los orificios de la válvula y la naturaleza de la fuerza de fricción entre las paredes del cilindro y el pistón, dificultan la obtención de modelos matemáticos exactos y el control de los sistemas neumáticos con alta precisión. Experimentos fueron llevados a cabo con un cilindro sin vástago de 25 mm de diámetro y una válvula de control proporcional de 5 puertos -3 vías. En este artículo, proponemos una estrategia de control de posicionamiento robusta para solucionar el problema de un sistema de servo posicionamiento neumático. El enfoque es novedoso en el sentido de que tiene en cuenta las no linealidades inherentes a los sistemas de servo posicionamiento neumático y considera posición, velocidad y diferencia de presiones en las cámaras del cilindro neumático como estados de retroalimentación.  La estrategia de control propuesta es implementada en simulación y sobre el sistema real. Los resultados experimentales de la implementación de la estrategia en el sistema de servo-posicionamiento  neumático muestran un alto desempeño en el control de seguimiento de posición