Kuldip S. Rattan

Adaptive control of a single-link flexible manipulator

A method for controlling single-link lightweight flexible manipulators is proposed. The objective is to control the tip position of the flexible manipulator in the presence of joint friction and changes in payload. Both linear and nonlinear frictions are overcome by using a very robust control scheme for flexible manipulators. The control scheme is based on two nested feedback loops: an inner loop, to control the position of the motor, and an outer loop, to control the tip position. Compensation for changes in load is achieved by decoupling the dynamics of the system and then applying a very simple adaptive control for the tip position. This results in a simple control law that needs minimal computing effort and, thus, can be used for real-time control of the flexible arms. >

Vibration control of a coordinate measuring machine

A comparative study of two vibration reduction schemes, the command preshaping technique and the feedforward control technique, is presented. The objective is to drive the end-point of a coordinate measuring machine along a commanded trajectory without any oscillations at the end-point. This is achieved by designing appropriate controllers for the system based on a robust control scheme. This scheme consists of two nested feedback loops-an inner loop to control the motor position and an outer loop to control the position of the end-point. The controllers based on the two vibration reduction schemes are designed for the outer loop to make the system vibration-free. It is shown that the command preshaping scheme is a special case of the feedforward control scheme. The design method is illustrated with a numerical example.<<ETX>>

Modeling and control of single-link flexible arms with lumped masses

This paper deals with the modeling and control of a special class of single-link flexible arms. These arms consist of flexible massless structures having some masses concentrated at certain points of the beam. In this paper, the dynamic model of such flexible arms is dewloped and some of the control properties are deduced. A robust control scheme to remove the effects of friction in the joins is proposed. The control scheme consists of two nested feedback loops, an inner loop to control the position of the motor and an outer loop to control the tip position. The inner loop is described in other publications. A simple fedforward-feedback controller is designed for the outer loop to driw the beam accurately along a desired trajectoty. Effects of the changes in the tip’s mass are studied. This modeling and control method is then generalized to the distributed-mass flexible beam case. Finally, experimentaf results are presented. This paper deals with the modeling and control of a special class of single-link, lumped-mass, flexible arms. These arms consist of massless flexible structures that have masses concentrated at certain points of the beam (see Fig. 1). Although the translations of these masses produce stresses in the flexible structure, their rotations do not generate any torque in the beam. Therefore, the number of vibrational modes in the structure coincides with the number of lumped masses. Book (1979) studied the case of two rigid masses connected by a chain of massless beams having an arbitrary number of rotation joints. Our problem differs from this in the sense that our structure has only one rotation joint and an arbitrary number of lumped masses. These two particular structures are studied because: Some lightweight robots and other applications can be reasonably approximated by these models. Their dynamics may be easily modeled as compared to distributed-mass flexible arms. Interesting properties for the control of flexible arms are deduced from their dynamic models. A method to control these arms is inferred from the structure of the model. The influence of changes in the tip’s mass are easily characterized. Given a distributed-mass flexible arm, there always exits a truncated dynamic model which is of the same form as the lumped-mass flexible arm model and which reproduces the dynamics of the measured variables. This allows us to generate the above mentioned control method to the case of distributed-mass flexible arms. - Contributed by the Dynamic Systems and Control Division for publication

Hybrid fuzzy logic PID controller

This paper investigates two fuzzy logic PID controllers that use simplified design schemes. Fuzzy logic PD and PI controllers are effective for many control problems but lack the advantages of the fuzzy PID controller. Design methodologies are in their infancy and still somewhat intuitive. Fuzzy controllers use a rule base to describe relationships between the input variables. Implementation of a detailed rule base increases in complexity as the number of input variables grow and the ranges of operation for the variables become more defined. We propose a hybrid fuzzy PID controller which takes advantage of the properties of the fuzzy PI and PD controllers and a second method which adds the fuzzy PD control action to the integral control action. The effectiveness of the two PID fuzzy controller implementations are illustrated with examples.<<ETX>>

Control of flexible arms with friction in the joints

The control of flexible arms with friction in the joints is studied. A method to identify the dynamics of a flexible arm from its frequency response (which is strongly distorted by Coulombs friction) is proposed. A robust control scheme that minimizes the effects of this friction is presented. The scheme consists of two nested feedback loops: an inner loop to control the motor position and an outer loop to control the tip position. It is shown that a proper design of the inner loop eliminates the effects of friction while controlling the tip position and significantly simplifies the design of the outer loop. The proposed scheme is applied to a class of lightweight flexible arms, and the experiments show that the control scheme results in a simple controller. As a result, the computations are minimized and, thus, high sampling rates may be used. >

Fuzzy logic control of a pneumatic muscle system using a linearing control scheme

A linearizing control scheme for a highly nonlinear pneumatic muscle (PM) system is presented in this paper. Linearizing controllers have been widely used in the control of robotic systems. Since PM is a highly nonlinear system, the concept of linearizing control can be extended to the control of these muscles. Pneumatic muscle has air pressure as its input and the output is a displacement of the muscle. The system is considered to be a mass-spring-damper system with a nonlinear damper and a spring. This nonlinearity makes the design of a mathematical controller more difficult. The scheme presented in this paper uses fuzzy logic to implement the controller. The controller has a model-based portion and a servo-based portion. The model-based portion cancels all the nonlinearities caused by the nonlinear damper and spring. Therefore, the system as seen by the servo-based portion is linear, which can then be controlled using a linear PID controller. The controller is conceptually simple but exhibited superior tracking capability.

Adaptive control of a single-link flexible manipulator in the presence of joint friction and load changes

A method for controlling single-link lightweight flexible manipulators is proposed. The objective is to control the tip position of the flexible manipulator in the presence of joint friction and changes in payload. Both linear and nonlinear frictions are overcome by using a very robust control scheme for flexible manipulators. The control scheme is based on two nested feedback loops: an inner loop, to control the position of the motor, and an outer loop, to control the tip position. Compensation for changes in load is achieved by decoupling the dynamics of the system and then applying a very simple adaptive control for the tip position. This results in a simple control law that needs minimal computing effort and, thus, can be used for real-time control of the flexible arms.<<ETX>>

Feedforward control of a non-linear pneumatic muscle system using fuzzy logic

Inverse dynamics is a commonly used technique in the control of dynamic systems. A fuzzy inverse dynamics controller (feedforward control) for a Pneumatic Muscle system is designed using two methods: Weighted Average and the Least Squared Error. Both methods use data collected from the system. The inverse model obtained using the two methods are tested for its trajectory tracking capabilities and the results are compared. Simulation results show that the feedforward controller obtained using Least Squared Error method has better trajectory tracking capabilities than the weighted average scheme.

Trajectory tracking control of a pneumatic muscle system using fuzzy logic

Pneumatic muscle (PM) system was first developed by McKibben in the 1950s as soft actuators in artificial limbs and became commercially available in the 1980s. They have since been used as actuators in high-tech robotic applications and in physical therapy for functional recovery since they are extremely safe in human presence compared to electric and hydraulic actuators. A high power to weight and power to volume ratios make the PM a very light yet powerful actuator. However, PM is highly nonlinear in nature due to its construction and mechanical properties and hence, they are difficult to control using a linear controller. Fuzzy logic is a good nonlinear modeling approach, since it uses fuzzy rules to handle nonlinearities. A fuzzy logic based feedforward controller (inverse dynamics) and feedback linearizing control schemes are proposed in this paper. Controllers are designed using data obtained from the PM system, and the design does not require a mathematical model. The PM parameters can change over time and varying operating conditions. Hence, an adaptive fuzzy algorithm is used to tune the fuzzy models to capture the parameter changes. The proposed control schemes are tested for its trajectory tracking capabilities and are found to yield excellent results.

Implementation of a fuzzy logic controller on an FPGA using VHDL

Implementation of a fuzzy logic controller on an FPGA using VHDL is presented in this paper. The basic components of the fuzzy logic controller are designed using VHDL and a Xilinx virtex FPGA is used for implementation. The fuzzy logic controller with an 8-bit input, 8-bit output is tested by controlling single disk of an ECP torsional plant.