Investigations of Model-Free Sliding Mode Control Algorithms including Application to Autonomous Quadrotor Flight

Sliding mode control is a robust nonlinear control algorithm that has been used to implement tracking controllers for unmanned aircraft systems that are robust to modeling uncertainty and exogenous disturbances, thereby providing excellent performance for autonomous operation. A significant advance in the application of sliding mode control for unmanned aircraft systems would be adaptation of a model-free sliding mode control algorithm, since the most complex and time-consuming aspect of implementation of sliding mode control is the derivation of the control law with incorporation of the system model, a process required to be performed for each individual application of sliding mode control. The performance of four different model-free sliding mode control algorithms was compared in simulation using a variety of aerial system models and real-world disturbances (e.g. the effects of discretization and state estimation). The two best performing algorithms were shown to exhibit very similar behavior. These two algorithms were implemented on a quadrotor (both in simulation and using real-world hardware) and the performance was compared to a traditional PID-based controller using the same state estimation algorithm and control setup. Simulation results show the model-free sliding mode control algorithms exhibit similar performance to PID controllers without the tedious tuning process. Comparison between the two model-free sliding mode control algorithms showed very similar performance as measured by the quadratic means of tracking errors. Flight testing showed that while a model-free sliding mode control algorithm is capable of controlling realworld hardware, further characterization and significant improvements are required before it is a viable alternative to conventional control algorithms. Large tracking errors were observed for both the model-free sliding mode control and PID based flight controllers and the performance was characterized as unacceptable for most applications. The poor performance of both controllers suggests tracking errors could be attributed to errors in state estimation, which effectively introduce unknown dynamics into the feedback loop. Further testing with improved state estimation would allow for more conclusions to be drawn about the performance characteristics of the model-free sliding mode control algorithms

SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS

This thesis discusses the empirical modeling using system identification technique and the implementation of a linear model predictive control with focus on interacting series processes. In general, a structure involving a series of systems occurs often in process plants that include processing sequences such as feed heat exchanger, chemical reactor, product cooling, and product separation. The study is carried out by experimental works using the gaseous pilot plant as the process. The gaseous pilot plant exhibits the typical dynamic of an interacting series process, where the strong interaction between upstream and downstream properties occurs in both ways. The subspace system identification method is used to estimate the linear model parameters. The developed model is designed to be robust against plant nonlinearities. The plant dynamics is first derived from mass and momentum balances of an ideal gas. To provide good estimations, two kinds of input signals are considered, and three methods are taken into account to determine the model order. Two model structures are examined. The model validation is conducted in open-loop and in closed-loop control system. Real-time implementation of a linear model predictive control is also studied. Rapid prototyping of such controller is developed using the available equipments and software tools. The study includes the tuning of the controller in a heuristic way and the strategy to combine two kinds of control algorithm in the control system. A simple set of guidelines for tuning the model predictive controller is proposed. Several important issues in the identification process and real-time implementation of model predictive control algorithm are also discussed. The proposed method has been successfully demonstrated on a pilot plant and a number of key results obtained in the development process are presented

Neural Networks for Modeling and Control of Particle Accelerators

We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.Comment: 21 p

1-Bit processing based model predictive control for fractionated satellite missions

In this thesis, a 1-bit processing based Model Predictive Control (OBMPC) structure is proposed for a fractionated satellite attitude control mission. Despite the appealing advantages of the MPC algorithm towards constrained MIMO control applications, implementing the MPC algorithm onboard a small satellite is certainly challenging due to the limited onboard resources. The proposed design is based on the 1-bit processing concept, which takes advantage of the affine relation between the 1-bit state feedback and multi-bit parameters to implement a multiplier free MPC controller. As multipliers are the major power consumer in online optimization, the OBMPC structure is proven to be more efficient in comparison to the conventional MPC implementation in term of power and circuit complexity. The system is in digital control nature, affected by quantization noise introduced by Δ∑ modulators. The stability issues and practical design criteria are also discussed in this work. Some other aspects are considered in this work to complete the control system. Firstly, the implementation of the OBMPC system relies on the 1-bit state feedbacks. Hence, 1-bit sensing components are needed to implement the OBMPC system. While the ∆∑ modulator based Microelectromechanical systems (MEMS) gyroscope is considered in this work, it is possible to implement this concept into other sensing components. Secondly, as the proposed attitude mission is based on the wireless inter-satellite link (ISL), a state estimator is required. However, conventional state estimators will once again introduce multi-bit signals, and compromise the simple, direct implementation of the OBMPC controller. Therefore, the 1-bit state estimator is also designed in this work to satisfy the requirements of the proposed fractionated attitude control mission. The simulation for the OBMPC is based on a 2U CubeSat model in a fractionated satellite structure, in which the payload and actuators are separated from the controller and controlled via the ISL. Matlab simulations and FPGA implementation based performance analysis shows that the OBMPC is feasible for fractionated satellite missions and is advantageous over the conventional MPC controllers

Design and implementation of event-based multi-rate controllers for networked control systems

Tesis por compendio[ES] Con esta tesis se pretende dar solución a algunos de los problemas más habituales que aparecen en los Sistemas de control basados en red (NCS) como son los retardos variables en el tiempo, las pérdidas y el desorden de paquetes, y la restricción de ancho de banda y de recursos computacionales y energéticos de los dispositivos que forman parte del sistema de control. Para ello se ha planteado la integración de técnicas de control multifrecuencial, de control basado en paquetes, de control basado en predictor y de control basado en eventos. Los diseños de control realizados se han simulado utilizando Matlab-Simulink y Truetime, se ha analizado su estabilidad mediante LMIs y QFT, y se han validado experimentalmente en un péndulo invertido, un robot cartesiano 3D y en robots móviles de bajo coste. El artículo 1 aborda el control basado en eventos, el cual minimiza el ancho de banda consumido en el NCS mediante un control basado en eventos periódicos y presenta un método para obtener sus parámetros óptimos para el sistema específico en que se utilice. Los artículos 2, 4 y 6 añaden el control basado en paquetes, así como el control multifrecuencia, que aborda problemas de falta de datos por bajo uso del sensor y los retardos, pérdidas y desórdenes de paquetes en la red. También afrontan, mediante tecnicas de predicción basadas en un filtro de Kalman multifrecuencia variable en el tiempo, los problemas de ruido y perturbaciones, así como la observación de los estados completos del sistema. El artículo 7 hace frente a un modelo no lineal que utiliza las anteriores soluciones junto con un filtro de Kalman extendido para presentar otro tipo de estructura para un vehículo autónomo que, gracias a la información futura obtenida mediante estas técnicas, puede realizar de forma remota tareas de alto nivel como es la toma de decisiones y la monitorización de variables. Los artículos 3 y 5, presentan una forma de obtener y analizar la respuesta en frecuencia de sistemas SISO multifrecuencia y estudian su comportamiento ante ciertas incertidumbres o problemas en la red haciendo uso de procedimientos QFT.[CA] Amb aquesta tesi es pretén donar solució a alguns dels problemes més habituals que apareixen als Sistemes de Control Basats en xarxa (NCS) com son els retards d'accés i transferència variables en el temps, les pèrdues y desordenament de paquets, i la restricció d'ampli de banda així com de recursos computacionals i energètics dels dispositius que foment part del sistema de control. Per tal de resoldre'ls s'ha plantejat la integració de tècniques de control multifreqüencial, de control basat en paquets, de control basat en predictor i de control basat en events. Els dissenys de control realitzats s'han simulat fent ús de Matlab-Simulink i de TrueTime, s'ha analitzat la seua estabilitat mitjançant LMIs i QFT, i s'han validat experimentalment en un pèndul invertit, un robot cartesià 3D i en robots mòbils de baix cost. L'article 1 aborda el control basat en events, el qual minimitza l'ampli de banda consumit a l'NCS mitjançant un control basat en events periòdics i presenta un mètode per a obtindré els seus paràmetres òptims per al sistema específic en el qual s'utilitza. Els articles 2, 4 i 6 afegeixen el control basat en paquets, així com el control multifreqüència, que aborda problemes de falta de dades per el baix us del sensor i els retards, pèrdues i desordre de paquets en la xarxa. També afronten, mitjançant tècniques de predicció basades en un filtre de Kalman multifreqüència variable en el temps. Els problemes de soroll i pertorbacions, així com la observació dels estats complets del sistema. L'article 7 fa referència a un model no lineal que utilitza les anteriors solucions junt a un filtre de Kalman estès per a presentar altre tipus d'estructura per a un vehicle autònom que, gracies a la informació futura obtinguda mitjançant aquestes tècniques, pot realitzar de manera remota tasques d'alt nivell com son la presa de decisions i la monitorització de variables. Els articles 3 y 5 presenten la manera d'obtindre i analitzar la resposta en frequencia de sistemes SISO multifreqüència i estudien el seu comportament front a certes incerteses o problemes en la xarxa fent us de procediments QFT.[EN] This thesis attempts to solve some of the most frequent issues that appear in Networked Control Systems (NCS), such as time-varying delays, packet losses and packet disorders and the bandwidth limitation. Other frequent problems are scarce computational and energy resources of the local system devices. Thus, it is proposed to integrate multirate control, packet-based control, predictor-based control and event-based control techniques. The control designs have been simulated using Matlab-Simulink and Truetime, the stability has been analysed by LMIs and QFT, and the experimental validation has been done on an inverted pendulum, a 3D cartesian robot and in low-cost mobile robots. Paper 1 addresses event-based control, which minimizes the bandwidth consumed in NCS through a periodic event-triggered control and presents a method to obtain the optimal parameters for the specific system used. Papers 2, 4 and 6 include packet-based control and multirate control, addressing problems such as network delays, packet dropouts and packet disorders, and the scarce data due to low sensor usage in order to save battery in sensing tasks and transmissions of the sensed data. Also addressed, is how despite the existence of measurement noise and disturbances, time-varying dual-rate Kalman filter based prediction techniques observe the complete state of the system. Paper 7 tackles a non-linear model that uses all the previous solutions together with an extended Kalman filter to present another type of structure for an autonomous vehicle that, due to future information obtained through these techniques, can remotely carry out high level tasks, such as decision making and monitoring of variables. Papers 3 and 5, present a method for obtaining and analyzing the SISO dual-rate frequency response and using QFT procedures to study its behavior when faced with specific uncertainties or network problems.This work was supported by the Spanish Ministerio de Economía y Competitividad under Grant referenced TEC2012-31506.Alcaina Acosta, JJ. (2020). Design and implementation of event-based multi-rate controllers for networked control systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/159884TESISCompendi

Distributed Control of HVAC&R Networks

Heating, ventilation, air conditioning, and refrigeration (HVAC&R) systems are a major component of worldwide energy consumption, and frequently consist of complex networks of interconnected components. The ubiquitous nature of these systems suggests that improvements in their energy efficiency characteristics can have significant impact on global energy consumption. The complexity of the systems, however, means that decentralized control schemes will not always suffice to balance competing goals of energy efficiency and occupant comfort and safety. This dissertation proposes control solutions for three facets of this problem. The first is a cascaded control architecture for actuators, such as electronic expansion valves, that provides excellent disturbance rejection and setpoint tracking characteristics, as well as partial nonlinearity compensation without a compensation model. The second solution is a hierarchical control architecture for multiple-evaporator vapor compression systems that uses model predictive control (MPC) at both the supervisory and component levels. The controllers leverage the characteristics of MPC to balance energy efficiency with occupant comfort. Since the local controllers are decentralized, the architecture retains a degree of modularity—changing one component does not require changing all controllers. The final contribution is a new distributed optimization algorithm that is rooted in distributed MPC and is especially motivated by HVAC&R systems. This algorithm allows local level optimizers to iterate to a centralized solution. The optimizers have no knowledge of any plant other than the plant they are associated with, and only need to communicate with their immediate neighbors. The efficacy of the algorithm is displayed with two sets of examples. One example is simulation based, wherein a building is modeled in the EnergyPlus software suite. The other is an experimental example. In this example, the algorithm is applied to a multiple evaporator vapor compression system. In both cases the design method is discussed, and the ability of the algorithm to reduce energy consumption when properly applied is demonstrated