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

Implementation of Iterative Learning Control on a Pneumatic Actuator.

Masters Degree. University of KwaZulu-Natal, Durban.Pneumatic systems play a pivotal role in many industrial applications, such as in petrochemical industries, steel manufacturing, car manufacturing and food industries. Besides industrial applications, pneumatic systems have also been used in many robotic systems. Nevertheless, a pneumatic system contains different nonlinear and uncertain behaviour due to gas compression, gas leakage, attenuation of the air in pipes and frictional forces in mechanical parts, which increase the system’s dynamic orders. Therefore, modelling a pneumatic system tends to be complicated and challenges the design of the controller for such a system. As a result, employing an effective control mechanism to precisely control a pneumatic system for achieving the required performance is essential. A desirable controller for a pneumatic system should be capable of learning the dynamics of the system and adjusting the control signal accordingly. In this study, a learning control scheme to overcome the highlighted nonlinearity problems is suggested. Many industrial processes are repetitive, and it is reasonable to make use of previously acquired data to improve a controller’s convergence and robustness. An Iterative Learning Control (ILC) algorithm uses information from previous repetitions to learn about the system’s dynamics. The ILC algorithm characteristics are beneficial in real-time control given its short time requirements for responding to input changes. Cylinder-piston actuators are the most common pneumatic systems, which translate the air pressure force into a linear mechanical motion. In industrial automation and robotics, linear pneumatic actuators have a wide range of applications, from load positioning to pneumatic muscles in robots. Therefore, the aim of this research is to study the performance of ILC techniques in position control of the rod in a pneumatic position-cylinder system. Based on theoretical analysis, the design of an ILC is discussed, showing that the controller can satisfactorily overcome nonlinearities and uncertainties in the system without needing any prior knowledge of the system’s model. The controller has been designed in such a way to even work on non-iterative processes. The performance of the ILC-controlled system is compared with a well-tuned PID controller, showing a faster and more accurate response

Pneumatic motion control systems for modular robots

This thesis describes a research study in the design, implementation, evaluation and commercialisation of pneumatic motion control systems for modular robots. The research programme was conducted as part of a collaborative study, sponsored by the Science and Engineering Research Council, between Loughborough University and Martonair (UK) Limited. Microprocessor based motion control strategies have been used to produce low cost pneumatic servo-drives which can be used for 'point-to-point' positioning of payloads. Software based realtime control strategies have evolved which accomplish servo-controlled positioning while compensating for drive system non-linearities and time delays. The application of novel compensation techniques has resulted in a significant improvement in both the static and dynamic performance of the drive. A theoretical foundation is presented based on a linearised model of a pneumatic actuator, servo-valve, and load system. The thesis describes the design and evolution of microprocessor based hardware and software for motion control of pneumatic drives. A British Standards based test-facility has allowed control strategies to be evaluated with reference to standard performance criteria. It is demonstrated in this research study that the dynamic and static performance characteristics of a pneumatic motion control system can be dramatically improved by applying appropriate software based realtime control strategies. This makes the application of computer controlled pneumatic servos in manufacturing very attractive with cost performance ratios which match or better alternative drive technologies. The research study has led to commercial products (marketed by Martonair Ltd), in which realtime control algorithms implementing these control strategy designs are executed within a microprocessor based motion controller

Pneumatic servo position control optimization using adaptive-domain prescribed performance control with evolutionary mating algorithm

Pneumatic servo systems face challenges such as friction, compressibility, and nonlinear dynamics, necessitating advanced control techniques. Research suggests model-based, model-free, hybrid, and optimization-based methods have their strengths. Therefore, this study presents an optimal control strategy using Adaptive Domain Prescribed Performance Control (AD-PPC) cascaded with PID and optimized using the Evolutionary Mating Algorithm (EMA) for a pneumatic servo system (PSS). The goal is to achieve faster transient control and stable rod-piston positioning with minimal friction through the hysteresis phenomenon of the targeted proportional valve-controlled double-acting pneumatic cylinder (PPVDC) representing the PSS. The novel EMA optimizes the cascaded controller based on the tracking error as its objective function. Simulation studies verify the proposed AD-PPC-PID controller with the PPVDC model plant, iteratively optimized by the EMA. The analytical study compares this setup's control system and optimization model with the same control system model using alternative optimization methods. The testing employs step and multi-step signals for PPVDC's rod-piston position input. Results show that the EMA-tuned AD-PPC-PID outperforms AD-PPC-PID controller with other optimizers. For both input trajectory tests, EMA-tuned AD-PPC-PID shows faster response times, with average improvements of 30 % in settling times and 70 % in tracking performance metrics compared to other optimizers, making it robust for nonlinear system applications like PPVDC rod-piston positioning

A CENTER MANIFOLD THEORY-BASED APPROACH TO THE STABILITY ANALYSIS OF STATE FEEDBACK TAKAGI-SUGENO-KANG FUZZY CONTROL SYSTEMS

The aim of this paper is to propose a stability analysis approach based on the application of the center manifold theory and applied to state feedback Takagi-Sugeno-Kang fuzzy control systems. The approach is built upon a similar approach developed for Mamdani fuzzy controllers. It starts with a linearized mathematical model of the process that is accepted to belong to the family of single input second-order nonlinear systems which are linear with respect to the control signal. In addition, smooth right-hand terms of the state-space equations that model the processes are assumed. The paper includes the validation of the approach by application to stable state feedback Takagi-Sugeno-Kang fuzzy control system for the position control of an electro-hydraulic servo-system

Volume 3 – Conference: Thursday, March 10

10. Internationales Fluidtechnisches Kolloquiu

Research on parallel control of CMAC and PD based on U model

In this paper, the nonlinear U model with time-varying coefficients is investigated and the transformation of the nonlinear model is accomplished by the Newton iterative algorithm. Based on the nonlinear U model, a control algorithm with cerebellar model articulation controller and proportional derivative (PD) in parallel is proposed. The algorithm learns online through a neural network while optimizing the output of the PD, which ultimately enables the actual output of the system to track up to the desired output. Considering that the nonlinear object has the characteristic of rapid change with time, the article improves the PD algorithm to nonlinear PD control algorithm to complete the design of the system. The algorithm automatically adjusts the weights according to the error magnitude to complete the controller parameter adjustment, thus reducing the error of the system. The simulation results show that the nonlinear PD algorithm is better than the PD algorithm, meanwhile, the tracking speed and control precision of the system are improved