This paper presents sliding mode controller design based on decoupling approach for multivariable process. The performance of proposed controller is experimentally verified on multivariable coupled tank system. The controller and decoupler are designed from process model obtained from fundamentals and experimental step response data. SMC is designed using linear sliding surface and stability of the system can be approximately analyzed via Lyapunov function method. A process decoupled through decouplers consisting higher order elements represented in the form of first-order-plus-dead-time (FOPDT) model using model reduction method. The closed-loop system performance and robustness is verified using Matlab/Simulink and NI DAQ card interface with multi-variable coupled tank process. Thus the proposed method is effective despite the effect of exogenous disturbance.

Design of SMC with decoupler for multi-variable coupled tank process

Industrial processes governed by automatic controllers can be subject to failures. Their incorrect operation can cause economic losses, workers’ hazards, inconvenience for users, etc. Moreover, automation of processes by means of automatic control loops, although permitted freeing human operators from manual control and operation, has not immunized them from failures. A way to enhance their reliability is to provide them with tolerance mechanisms to face these failures (Blanke et al., 2001). It is understood as 'failure' every change in the behavior of any component of the system (non-permitted deviation of any characteristic property or parameter), so the system cannot satisfy the function it has been designed for (Blanke et al., 2006). Control loops can hide failures preventing their detection to the point of causing irreparable damages forcing to stop the system or process. Because of this, there is a growing need and concern for developing control systems capable of acceptable operation even in the case of failures, also being able to stop the process before irreparable damages arise. This kind of control systems are called 'failure tolerant': control systems that can, in the one hand, detect incipient failures in sensors and/ or actuators; and, in the other, adapt control laws quickly to preserve the specified operation in terms of production quality, safety, etc. (Bonivento et al., 2004). Figure 1 shows the block diagram corresponding to a fault-tolerant control system. (Blanke et al., 2006). In this chapter the development of a simulation environment applied to the study of fault tolerant control systems for robotic manipulators by employing MatLab-Simulink programming tools is presented. By using this simulator is possible to represent the behavior of a manipulator: in the presence of a failure into one of its actuators and the status of correction of such failure, through an active fault tolerant control system. The end-effector Cartesian trajectories and the evolution of the joints of the manipulator are provided by means of animations and graphics in a comfortable and intuitive programming environment.

/pdf/development-of-a-simulation-environment-applied-to-the-study-2tjfqr7xxu.pdf

Development of a Simulation Environment Applied to the Study of Fault-Tolerant Control Systems in Robotic Manipulators. Theoretical and Practical Comparisons

Sliding Mode Control (SMC) as a mode of the Variable Structure Control (VSC) is known as an excellent robust control strategy in the field of uncertain and nonlinear control with high performance. However, chattering and process model dependency as main problems of the original SMC constrain its application. Also, in multivariable nonlinear process control, the interaction among the manipulated and controlled variables can degrade the performance of the controller. The objective of this paper is to design a new model-free Fuzzy Sliding Mode Control (FSMC) to solve these problems in MIMO process control. In this strategy, the equivalent –like term of the SMC’s control law is estimated using a self-tuned MIMO fuzzy logic inference system in order to overcome the dependency of the SMC to the process model and to reject undesirable effect of interaction toward improvement of robustness. Moreover, in design of linear sliding variables for switching term of the SMC, all states error are associated to lessen the interaction effect. Finally, the proposed strategy has been evaluated through implementation on a warm water tank system equipped with two manipulated servo valve to control temperature and water level. This system is nonlinear and affected by unknown disturbances. The results reveal that the purposed scheme is superior in servo tracking and unknown disturbance rejection performances in comparison with the classical PI control.

/pdf/a-new-approach-in-design-of-model-free-fuzzy-sliding-mode-x0ck5h05fd.pdf

A New Approach in Design of Model-free Fuzzy Sliding Mode Controller for Multivariable Chemical Processes

A sliding mode controller design method is proposed for multivariable systems. The method is based on dynamic decouplers to improve performance of multi loop control systems by compensating process interactions. A Proportional-Integral-Derivative (PID) sliding surface is used for sliding mode control. A process is decoupled through dynamic decouplers and each higher order element of decoupled subsystem is represented in the form of first-order-plus-dead-time (FOPDT) model using model reduction method. The sliding mode control law is derived from the Lyapunov stability approach and tuning parameters are computed for the sliding mode controller and PID sliding surface. Typical multivariable industrial processes including those have weak, moderate or strong interaction modes are employed to demonstrate the effectiveness and simplicity of the proposed method.

Design decentralized sliding mode controllers with dynamic decouplers for TITO processes

Resumen en: This paper introduces the approach of sliding mode control SMC which can be used for a large class of multivariable processes. The process studied in th...

Sliding mode control for multivariable processes

Resumen es: En este articulo se presenta la estabilizacion simultanea con multiples dominios de estabilidad como una tecnica aplicada al control tolerante a fallas ...

Control tolerante a fallas mediante técnicas de estabilizaciónsimultanea con múltiples dominios de estabilidad.

This paper describes the software PGIBOT Mat for modeling of industrial robots, developed with Matlab Graphical User Interface (GUI) as a tool to facilitate the use of a robotic Toolbox and a way to generate simulations files in RoboWorks 3D environment. The developed Toolbox can be applied to nine types of homogenous transformations, determine the transformations which define the relative movement among consecutive links of kinematics chain, perform the direct kinematics study and simulate the operation of a Teach Pendant in the planning of simple tasks for Industrial Robots (IR) with six or less limiting degrees.

/pdf/diseno-de-software-para-la-modelacion-de-manipuladores-con-45t5oi5yr6.pdf

Diseño de software para la modelación de manipuladores con Matlab y simulación 3D con RoboWorks

This paper introduces the approach of sliding mode control SMC which can be used for a large class of multivariable processes. The process studied in this work is modeled as a first order system with a dead zone. The designed controller is evaluated in both, the level and temperature control of a water tank system. The process consists of a tank with two servo valves and two sensors for the level and temperature measurement in the liquid level system. The controller is a computer implementation of SMC. The controller implementation and the instrumented system has shown better performance, for the different experimental conditions (i.e., disturbance and set points), compared with a PI controller.

/pdf/control-en-modo-deslizante-para-procesos-multivariable-1hmue1qih0.pdf

Control en modo deslizante para procesos multivariable

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Sliding mode control for multivariable processes

Control tolerante a fallas mediante técnicas de estabilizaciónsimultanea con múltiples dominios de estabilidad.

Diseño de software para la modelación de manipuladores con Matlab y simulación 3D con RoboWorks

Control en modo deslizante para procesos multivariable