An elastic net orthogonal forward regression algorithm

In this paper we propose an efficient two-level model identification method for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level to carry out simultaneous model selection and elastic net parameter estimation. The two regularization parameters in the elastic net are optimized using a particle swarm optimization (PSO) algorithm at the upper level by minimizing the leave one out (LOO) mean square error (LOOMSE). Illustrative examples are included to demonstrate the effectiveness of the new approaches.

Improved MATLAB GUIs for learning frequency response methods

The author developed two GUIs for asymptotic Bode plots and identification from such plots aimed at improving the learning of frequency response methods: these were presented at UKACC Control 2012. Student feedback and reflection by the author suggested various improvements to these GUIs, which have now been implemented. This paper reviews the earlier work, describes the improvements, and includes positive feedback from the students on the GUIs and how they have helped their understanding of the methods.

The cyber challenge: a robotics project to enthuse

Robotics is a key theme in many of the degrees offered in Systems Engineering. The topic has proved useful in attracting students to the University, and it also provides the basis of much practical and project work throughout the degrees. This paper focuses on one aspect, a Part 2 project in which students doing various degrees work together to develop a mobile robot which is controlled remotely to navigate an environment and perform specific tasks. In addition to providing practical experience of relevant academic topics, this project helps to contribute to key teaching and learning priorities including problem based learning, motivation and important employability skills.

Pose estimation of a humanoid robot using images from a mobile external camera

NOGUEIRA, Marcelo B. ; MEDEIROS, Adelardo A. D. ; ALSINA, Pablo J. Pose Estimation of a Humanoid Robot Using Images from an Mobile Extern Camera. In: IFAC WORKSHOP ON MULTIVEHICLE SYSTEMS, 2006, Salvador, BA. Anais... Salvador: MVS 2006, 2006.

Modeling and analysis of artificial neural networks applied in operations research

Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a massive number of these computational elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving problems related to operations research. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

An adaptive system based on artificial neural networks for NPK fluid fertilizer application

The application process of fluid fertilizers through variable rates implemented by classical techniques with feedback and conventional equipments can be inefficient or unstable. This paper proposes an open-loop control system based on artificial neural network of the type multilayer perceptron for the identification and control of the fertilizer flow rate. The network training is made by the algorithm of Levenberg-Marquardt with training data obtained from measurements. Preliminary results indicate a fast, stable and low cost control system for precision fanning. Copyright (C) 2000 IFAC.

Stochastic scheduling - A flow shop no wait application and solutions

Minimizing the makespan of a flow-shop no-wait (FSNW) schedule where the processing times are randomly distributed is an important NP-Complete Combinatorial Optimization Problem. In spite of this, it can be found only in very few papers in the literature. By considering the Start Interval Concept, this problem can be formulated, in a practical way, in function of the probability of the success in preserve FSNW constraints for all tasks execution. With this formulation, for the particular case with 3 machines, this paper presents different heuristics solutions: by integrating local optimization steps with insertion procedures and by using genetic algorithms for search the solution space. Computational results and performance evaluations are commented. Copyright (C) 1998 IFAC.

Linear quadratic Gaussian control of discrete-time Markov jump linear systems with horizon defined by stopping times

The linear quadratic Gaussian control of discrete-time Markov jump linear systems is addressed in this paper, first for state feedback, and also for dynamic output feedback using state estimation. in the model studied, the problem horizon is defined by a stopping time τ which represents either, the occurrence of a fix number N of failures or repairs (T N), or the occurrence of a crucial failure event (τ δ), after which the system paralyzed. From the constructive method used here a separation principle holds, and the solutions are given in terms of a Kalman filter and a state feedback sequence of controls. The control gains are obtained by recursions from a set of algebraic Riccati equations for the former case or by a coupled set of algebraic Riccati equation for the latter case. Copyright © 2005 IFAC.

Hybrid visual-driven decision support system in video monitor manufacturing

An intelligent system that emulates human decision behaviour based on visual data acquisition is proposed. The approach is useful in applications where images are used to supply information to specialists who will choose suitable actions. An artificial neural classifier aids a fuzzy decision support system to deal with uncertainty and imprecision present in available information. Advantages of both techniques are exploited complementarily. As an example, this method was applied in automatic focus checking and adjustment in video monitor manufacturing. Copyright © 2005 IFAC.

Towards intelligent manufacturing

This article describes the application of an Artificial Intelligence Planner in a robotized assembly cell that can be integrated to a Flexible Manufacturing System. The objective is to allow different products to be automatically assembled in a single production line with no pre-established assembly plans. The planner function is to generate action plans to the robot, in real time, from two input information: the initial state (disposition of parts of the product in line) and the final state (configuration of the assembled product). Copyright © 2007 IFAC.

Petri nets teaching in the Mechatronics Engineering course

The current solutions implanted in the majority of manufacturing systems controlled by PLCs were developed through the language of programming known as ladder. Such a language, easily learned and handled, shows to be efficient whenever the system to be implanted does not demand greater complexity of analyses. Bigger systems, presenting characteristics in which resource compartments, parallelism and synchronizing among processes are more frequent, demand the adoption of solutions differentiation. This article presents a teaching experience and practical application of Petri nets in a Mechatronics Engineering graduation course. Copyright © 2007 IFAC.

An efficient methodological approach in the didatic of automation applied to integrated manufacturing

This work presents challenges and solutions for the teaching and learning of automation applied to integrated manufacturing by means of a methodological approach based on techniques, tools and industrial equipment directly applicable in the industry. The approach was implemented in a control and automation engineering course divided into expositive and laboratory classes. Since the success of the approach is mainly from the practical activities, the article focus more on activities developed in laboratory than theorical classes. Copyright © 2007 IFAC.

Digital system design process automation using place/transition petri nets

The constant increase in digital systems complexity definitely demands the automation of the corresponding synthesis process. This paper presents a computational environment designed to produce both software and hardware implementations of a system. The tool for code generation has been named ACG8051. As for the hardware synthesis there has been produced a larger environment consisting of four programs, namely: PIPE2TAB, AGPS, TABELA, and TAB2VHDL. ACG8051 and PIPE2TAB use place/transition net descriptions from PIPE as inputs. ACG8051 is aimed at generating assembly code for the 8051 micro-controller. PIPE2TAB produces a tabular version of a Mealy type finite state machine of the system, its output is fed into AGPS that is used for state allocation. The resulting digital system is then input to TABELA, which minimizes control functions and outputs of the digital system. Finally, the output generated by TABELA is fed to TAB2VHDL that produces a VHDL description of the system at the register transfer level. Thus, we present here a set of tools designed to take a high-level description of a digital system, represented by a place/transition net, and produces as output both an assembly code that can be immediately run on an 8051 micro-controller, and a VHDL description that can be used to directly implement the hardware parts either on an FPGA or as an ASIC.

A maximum principle for infinite time asymptotically stable impulsive dynamic control systems

We consider an infinite horizon optimal impulsive control problems for which a given cost function is minimized by choosing control strategies driving the state to a point in a given closed set C ∞. We present necessary conditions of optimality in the form of a maximum principle for which the boundary condition of the adjoint variable is such that non-degeneracy due to the fact that the time horizon is infinite is ensured. These conditions are given for conventional systems in a first instance and then for impulsive control problems. They are proved by considering a family of approximating auxiliary interval conventional (without impulses) optimal control problems defined on an increasing sequence of finite time intervals. As far as we know, results of this kind have not been derived previously. © 2010 IFAC.