Max Suell Dutra

Depth control of remotely operated underwater vehicles using an adaptive fuzzy sliding mode controller

Sliding mode control, due to its robustness against modelling imprecisions and external disturbances, has been successfully employed to the dynamic positioning of remotely operated underwater vehicles. In order to improve the performance of the complete system, the discontinuity in the control law must be smoothed out to avoid the undesirable chattering effects. The adoption of a properly designed thin boundary layer has proven effective in completely eliminating chattering, however, leading to an inferior tracking performance. This paper describes the development of a depth control system for remotely operated underwater vehicles. The adopted approach is based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm for uncertainty/disturbance compensation. The stability and convergence properties of the closed-loop system are analytically proved using Lyapunov stability theory and Barbalats lemma. Numerical results are presented in order to demonstrate the control system performance.

An adaptive fuzzy sliding mode controller for remotely operated underwater vehicles

Sliding mode control is a very attractive control scheme because of its robustness against both structured and unstructured uncertainties as well as external disturbances. In this way, it has been widely employed for the dynamic positioning of remotely operated underwater vehicles. Nevertheless, in such situations the discontinuities in the control law must be smoothed out to avoid the undesirable chattering effects. The adoption of properly designed boundary layers has proven effective in completely eliminating chattering, however, leading to an inferior tracking performance. This work describes the development of a dynamic positioning system for remotely operated underwater vehicles. The adopted approach is primarily based on the sliding mode control strategy and enhanced by an adaptive fuzzy algorithm for uncertainty/disturbance compensation. Using the Lyapunov stability theory and Barbalats lemma, the boundedness and convergence properties of the closed-loop signals are analytically proven. The performance of the proposed control scheme is also evaluated by means of numerical simulations.

Sliding Mode Control with Adaptive Fuzzy Dead-Zone Compensation of an Electro-hydraulic Servo-System

Electro-hydraulic servo-systems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electro-hydraulic systems, due to their inherent nonlinear characteristics, cannot be easily obtained with conventional linear controllers. Most flow control valves can also exhibit some hard nonlinearities such as dead-zone due to valve spool overlap. This work describes the development of an adaptive fuzzy sliding mode controller for an electro-hydraulic system with unknown dead-zone. The boundedness and convergence properties of the closed-loop signals are proven using Lyapunov stability theory and Barbalat’s lemma. Numerical results are presented in order to demonstrate the control system performance.

Modeling of a bipedal locomotor using coupled nonlinear oscillators of Van der Pol

Abstract. Research to date points to an understanding of human biped locomotion that has been primarily experimental in nature largely due to the complexity of the process. In view of the new, exciting possibilities of programmed electrostimulation of artificial muscles to generate motion (locomotion), a critical study at the theoretical level is greatly warranted. There is strong evidence that many biological clocks consist of a population of mutually coupled oscillators [Pavlidis T (1973) Biological oscillators, Academic; Johnsson A (1978) Zur Biophysik biologischer Oszillatoren. In: Biophisik, Springer]. In this work, a form of bipedal locomotion is simulated by using mutually coupled nonlinear oscillators. A planar model, which includes three out of the six determinants of gait that characterize the human locomotion, was adopted.

Modeling of a bipedal robot using mutually coupled Rayleigh oscillators

Abstract.The objective of the work presented here was the modeling of a bipedal robot using a central pattern generator (CPG) formed by a set of mutually coupled Rayleigh oscillators. We analyzed a 2D model, with the three most important determinants of gait, that performs only motions parallel to the sagittal plane. Using oscillators with integer relation of frequency, we determined the transient motion and the stable limit cycles of the network formed by the three oscillators, showing the behavior of the knee angles and the hip angle. A comparison of the plotted graphs revealed that the system provided excellent results when compared to experimental analysis. Based on the results of the study, we come to the conclusion that the use of mutually coupled Rayleigh oscillators can represent an excellent method of signal generation, allowing their application for feedback control of a walking machine.

Dynamic Positioning of Underwater Robotic Vehicles with Thruster Dynamics Compensation

The development of accurate control systems for underwater robotic vehicles relies on the adequate compensation of thruster dynamics. Without compensation, the closed-loop positioning system can exhibit limit cycles. This undesired behaviour may compromise the overall system stability. In this work, a fuzzy sliding-mode compensation scheme is proposed for electrically actuated bladed thrusters, which are commonly employed in the dynamic positioning of underwater vehicles. The boundedness and convergence properties of the tracking error are analytically proven. The numerical results suggest that this approach shows a greatly improved performance when compared with an uncompensated counterpart.

Movement persuit control of an offshore automated platform via a RAM-based neural network

The reproduction of the movements of a ship by automated platforms, without the use of sensors providing exact data related to the numeric variables involved, is a non-trivial matter. The creation of an artificial vision system that can follow the cadence of said ship, in six axes of freedom, is the goal of this research. Considering that a real time response is a requisite in this case, it was decided to adopt a Boolean artificial neural network system that could identify and follow arbitrary interest points that could define, as a group, a model of the movement of an observed vessel. This paper describes the development of a prototype based on the Boolean perceptron model WiSARD (Wilkie, Stonham and Aleksanders Recognition Device), that is being implemented in the C programming language on a desktop computer using a regular webcam as input.

An adaptive fuzzy dead-zone compensation scheme and its application to electro-hydraulic systems

The dead-zone is one of the most common hard nonlinearities in industrial actuators and its presence may drastically compromise control systems stability and performance. Due to the possibility to express specialist knowledge in an algorithmic manner, fuzzy logic has been largely employed in the last decades to both control and identification of uncertain dynamical systems. In spite of the simplicity of this heuristic approach, in some situations a more rigorous mathematical treatment of the problem is required. In this work, an adaptive fuzzy controller is proposed for nonlinear systems subject to dead-zone input. The boundedness of all closed-loop signals and the convergence properties of the tracking error are proven using Lyapunov stability theory and Barbalats lemma. An application of this adaptive fuzzy scheme to an electro-hydraulic servo-system is introduced to illustrate the controller design method. Numerical results are also presented in order to demonstrate the control system performance.

Modelling of Bipedal Robots Using Coupled Nonlinear Oscillators

The first indications that the spinal marrow could contain the basic nervous system necessary to generate locomotion date back to the early 20th century. According to MackayLyons (2002), the existence of nets of nervous cells that produce specific rhythmic movements for a great number of vertebrates is something unquestionable. Nervous nets in the spinal marrow are capable of producing rhythmic movements, such as swimming, jumping, and walking, when isolated from the brain and sensorial entrances. These specialised nervous systems are known as nervous oscillators or central pattern generators (CPGs). Grillner (1985), Collins & Stewart (1993), Pearson (1993), and Collins & Richmond (1994) are some interesting works about the locomotion of vertebrates controlled by central pattern generators. According to Moraes (1999), the relation between spinal marrow and encephalus in the central nervous system of domestic animals is most significant than relation in human beings. This occurs because the most motor activities in the animals is performed by reflexes and not by the cerebral activity. In relation to the total activity of the central nervous system, it is estimate that exist approximately ten times more activity in the spinal marrow of dogs than in humans. However, the human locomotion is controlled, in part, by a central pattern generator, which is evidenced in the works as Calancie et al. (1994), Dimitrijevic et al. (1998) and Pinter & Dimitrijevic (1999). Coupled nonlinear oscillators can be used in control systems of locomotion as pattern generators similar to the pattern of human gait, providing the approach trajectories of the legs. The central pattern generator is composed of a set of mutually coupled nonlinear oscillators, where each oscillator generates angular signals of reference for the movement of the legs. Each oscillator has its proper amplitude, frequency and parameters, and coupling terms makes the linking to the other oscillators. Some previous works on central pattern generators formed by nonlinear oscillators, applied in the locomotion of bipedal robots, can be seen in Bay & Hemami (1987), Dutra (1995), Zielinska (1996), Dutra et al. (2003) and Pina Filho et al. (2005). The objective of this chapter is to present the modelling of a bipedal robot using a central pattern generator formed by a set of coupled nonlinear oscillators. We present some

Motion planning on Mobile Robots using Differential Flatness

One solution for the motion planning in a nonholonomic vehicle, described as mobile robot, is made in this paper. Using the boundary conditions, the desired trajectory is parameterized in a polynomial by means of a point to point steering algorithm. The system is drove trough the trajectory, using the Differential Flatness properties, calculating the input values in order to perform the movement. Simulations and results of the study are presented.