Intelligent control of nonlinear systems with actuator saturation using neural networks

Common actuator nonlinearities such as saturation, deadzone, backlash, and hysteresis are unavoidable in practical industrial control systems, such as computer numerical control (CNC) machines, xy-positioning tables, robot manipulators, overhead crane mechanisms, and more. When the actuator nonlinearities exist in control systems, they may exhibit relatively large steady-state tracking error or even oscillations, cause the closed-loop system instability, and degrade the overall system performance. Proportional-derivative (PD) controller has observed limit cycles if the actuator nonlinearity is not compensated well. The problems are particularly exacerbated when the required accuracy is high, as in micropositioning devices. Due to the non-analytic nature of the actuator nonlinear dynamics and the fact that the exact actuator nonlinear functions, namely operation uncertainty, are unknown, the saturation compensation research is a challenging and important topic with both theoretical and practical significance. Adaptive control can accommodate the system modeling, parametric, and environmental structural uncertainties. With the universal approximating property and learning capability of neural network (NN), it is appealing to develop adaptive NN-based saturation compensation scheme without explicit knowledge of actuator saturation nonlinearity. In this dissertation, intelligent anti-windup saturation compensation schemes in several scenarios of nonlinear systems are investigated. The nonlinear systems studied within this dissertation include the general nonlinear system in Brunovsky canonical form, a second order multi-input multi-output (MIMO) nonlinear system such as a robot manipulator, and an underactuated system-flexible robot system. The abovementioned methods assume the full states information is measurable and completely known. During the NN-based control law development, the imposed actuator saturation is assumed to be unknown and treated as the system input disturbance. The schemes that lead to stability, command following and disturbance rejection is rigorously proved, and verified using the nonlinear system models. On-line NN weights tuning law, the overall closed-loop performance, and the boundedness of the NN weights are rigorously derived and guaranteed based on Lyapunov approach. The NN saturation compensator is inserted into a feedforward path. The simulation conducted indicates that the proposed schemes can effectively compensate for the saturation nonlinearity in the presence of system uncertainty

Development of Motion Control Systems for Hydraulically Actuated Cranes with Hanging Loads

Automation has been used in industrial processes for several decades to increase efficiency and safety. Tasks that are either dull, dangerous, or dirty can often be performed by machines in a reliable manner. This may provide a reduced risk to human life, and will typically give a lower economic cost. Industrial robots are a prime example of this, and have seen extensive use in the automotive industry and manufacturing plants. While these machines have been employed in a wide variety of industries, heavy duty lifting and handling equipment such as hydraulic cranes have typically been manually operated. This provides an opportunity to investigate and develop control systems to push lifting equipment towards the same level of automation found in the aforementioned industries. The use of winches and hanging loads on cranes give a set of challenges not typically found on robots, which requires careful consideration of both the safety aspect and precision of the pendulum-like motion. Another difference from industrial robots is the type of actuation systems used. While robots use electric motors, the cranes discussed in this thesis use hydraulic cylinders. As such, the dynamics of the machines and the control system designmay differ significantly. In addition, hydraulic cranes may experience significant deflection when lifting heavy loads, arising from both structural flexibility and the compressibility of the hydraulic fluid. The work presented in this thesis focuses on motion control of hydraulically actuated cranes. Motion control is an important topic when developing automation systems, as moving from one position to another is a common requirement for automated lifting operations. A novel path controller operating in actuator space is developed, which takes advantage of the load-independent flow control valves typically found on hydraulically actuated cranes. By operating in actuator space the motion of each cylinder is inherently minimized. To counteract the pendulum-like motion of the hanging payload, a novel anti-swing controller is developed and experimentally verified. The anti-swing controller is able to suppress the motion from the hanging load to increase safety and precision. To tackle the challenges associated with the flexibility of the crane, a deflection compensator is developed and experimentally verified. The deflection compensator is able to counteract both the static deflection due to gravity and dynamic de ection due to motion. Further, the topic of adaptive feedforward control of pressure compensated cylinders has been investigated. A novel adaptive differential controller has been developed and experimentally verified, which adapts to system uncertainties in both directions of motion. Finally, the use of electro-hydrostatic actuators for motion control of cranes has been investigated using numerical time domain simulations. A novel concept is proposed and investigated using simulations.publishedVersio

Analysis of feedback control applied with command shaping to minimize residual vibration

Joint flexibility is a physical trait that affects all robotic systems to some degree. This characteristic has been shown to be very detrimental to the performance of these robotic systems when implementing fast point-to-point motion. During such motion, the robot will induce vibrations in its structure that will extend past the completion of the move. Many techniques have been applied over the years in order to minimize these residual vibrations. One such method is known as command shaping, which will construct the input profile so as to avoid exciting the natural frequencies of the system. This work seeks to extend this by analyzing how the feedback controller interacts with the input signal. Since a robotic manipulator is inherently nonlinear, this investigation is begun using a linear three-mass system that mimics the important dynamics of a two-link flexible-joint robot. A model of this three-mass system is derived and simulated in order to provide a new testbed for analyzing the problem of reducing residual vibration. It is shown that by appropriately designing the feedback controller so as to minimize the level of energy at the natural frequencies, lower residual vibration amplitudes are achieved. However, in some instances, these vibrations may take longer to settle out, which is directly correlated to the closed-loop damping of the system. This provides guidelines on how to appropriately construct a feedback controller so as to minimize residual vibration. Using this better understanding of the influence of the feedback, several different controllers are then tested on a two-link flexible-joint robot. The results of these experiments show correlation with the results obtained from the linear system analysis completed, and the trends are now better understood by applying the knowledge gained from the three-mass system. With the influence of the feedback controller on the level of residual vibration that ensues from fast point-to-point motion identified, the separate problems of command shaping and feedback control are tied together so as to achieve even lower levels of residual vibration

Time Varying Compensator Design for Reconfigurable Structures Using Non-Collocated Feedback

Analysis and synthesis tools are developed to improved the dynamic performance of reconfigurable nonminimum phase, nonstrictly positive real-time variant systems. A novel Spline Varying Optimal (SVO) controller is developed for the kinematic nonlinear system. There are several advantages to using the SVO controller, in which the spline function approximates the system model, observer, and controller gain. They are: The spline function approximation is simply connected, thus the SVO controller is more continuous than traditional gain scheduled controllers when implemented on a time varying plant; ft is easier for real-time implementations in storage and computational effort; where system identification is required, the spline function requires fewer experiments, namely four experiments; and initial startup estimator transients are eliminated. The SVO compensator was evaluated on a high fidelity simulation of the Shuttle Remote Manipulator System. The SVO controller demonstrated significant improvement over the present arm performance: (1) Damping level was improved by a factor of 3; and (2) Peak joint torque was reduced by a factor of 2 following Shuttle thruster firings

Adaptive Control

Adaptive control has been a remarkable field for industrial and academic research since 1950s. Since more and more adaptive algorithms are applied in various control applications, it is becoming very important for practical implementation. As it can be confirmed from the increasing number of conferences and journals on adaptive control topics, it is certain that the adaptive control is a significant guidance for technology development.The authors the chapters in this book are professionals in their areas and their recent research results are presented in this book which will also provide new ideas for improved performance of various control application problems

TIP trajectory tracking of flexible-joint manipulators

In most robot applications, the control of the manipulator’s end-effector along a specified desired trajectory is the main concern. In these applications, the end-effector (tip) of the manipulator is required to follow a given trajectory. Several methods have been so far proposed for the motion control of robot manipulators. However, most of these control methods ignore either joint friction or joint elasticity which can be caused by the transmission systems (e.g. belts and gearboxes). This study aims at development of a comprehensive control strategy for the tip-trajectory tracking of flexible-joint robot manipulators. While the proposed control strategy takes into account the effect of the friction and the elasticity in the joints, it also provides a highly accurate motion for the manipulator’s end-effector. During this study several approaches have been developed, implemented and verified experimentally/numerically for the tip trajectory tracking of robot manipulators. To compensate for the elasticity of the joints two methods have been proposed; they are a composite controller whose design is based on the singular perturbation theory and integral manifold concept, and a swarm controller which is a novel biologically-inspired controller and its concept is inspired by the movement of real biological systems such as flocks of birds and schools of fishes. To compensate for the friction in the joints two new approaches have been also introduced. They are a composite compensation strategy which consists of the non-linear dynamic LuGre model and a Proportional-Derivative (PD) compensator, and a novel friction compensation method whose design is based on the Work-Energy principle. Each of these proposed controllers has some advantages and drawbacks, and hence, depending on the application of the robot manipulator, they can be employed. For instance, the Work-Energy method has a simpler form than the LuGre-PD compensator and can be easily implemented in industrial applications, yet it provides less accuracy in friction compensation. In addition to design and develop new controllers for flexible-joint manipulators, another contribution of this work lays in the experimental verification of the proposed control strategies. For this purpose, experimental setups of a two-rigid-link flexible-joint and a single-rigid-link flexible-joint manipulators have been employed. The proposed controllers have been experimentally tested for different trajectories, velocities and several flexibilities of the joints. This ensures that the controllers are able to perform effectively at different trajectories and speeds. Besides developing control strategies for the flexible-joint manipulators, dynamic modeling and vibration suppression of flexible-link manipulators are other parts of this study. To derive dynamic equations for the flexible-link flexible-joint manipulators, the Lagrange method is used. The simulation results from Lagrange method are then confirmed by the finite element analysis (FEA) for different trajectories. To suppress the vibration of flexible manipulators during the manoeuvre, a collocated sensor-actuator is utilized, and a proportional control method is employed to adjust the voltage applied to the piezoelectric actuator. Based on the controllability of the states and using FEA, the optimum location of the piezoelectric along the manipulator is found. The effect of the controller’s gain and the delay between the input and output of the controller are also analyzed through a stability analysis

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Dynamic modelling and control of a flexible manoeuvring system.

In this research a twin rotor multi-input multi-output system (TRMS), which is a laboratory platform with 2 degrees of freedom (DOF) is considered. Although, the TRMS does not fly, it has a striking similarity with a helicopter, such as system nonlinearities and cross-coupled modes. Therefore, the TRMS can be perceived as an unconventional and complex "air vehicle" that poses formidable challenges in modelling, control design and analysis, and implementation. These issues constitute the scope of this research. Linear and nonlinear models for the vertical movement of the TRMS are obtained via system identification techniques using black-box modelling. The approach yields input-output models without a priori defined model structure or specific parameter settings reflecting any physical attributes of the system. Firstly, linear parametric models, characterising the TRMS in its hovering operation mode, are obtained using the potential of recursive least squares (RLS) estimation and genetic algorithms (GAs). Further, a nonlinear model using multi-layer perceptron (MLP) neural networks (NNs) is obtained. Such a high fidelity nonlinear model is often required for nonlinear system simulation studies and is commonly employed in the aerospace industry. Both time and frequency domain analyses are utilised to investigate and develop confidence in the models obtained. The frequency domain verification method is a useful tool in the validation of extracted parametric models. It allows high-fidelity verification of dynamic characteristics over a frequency range of interest. The resulting models are utilized in designing controllers for low frequency vibration suppression, development of suitable feedback control laws for set-point tracking, and design of augmented feedforward and feedback control schemes for both vibration suppression and set-point tracking performance. The modelling approaches presented here are shown to be suitable for modelling complex new generation air vehicles, whose flight mechanics are not well understood. Modelling of the TRMS revealed the presence of resonance modes, which are responsible for inducing unwanted vibrations in the system. Command shaping 11 control strategies are developed to reduce motion and uneven mass induced vibrations, produced by the main rotor during the vertical movement around the lateral axis of the TRMS rig. 2-impulse, 3-impulse and 4-impulse sequence input shapers and Iow-pass and band-stop digital filters are developed to shape the command signals such that the resonance modes are not overly excited. The effectiveness of this concept is then demonstrated in both simulation and real-time experimental environments in terms of level of vibration reduction using power spectral density profiles of the system response. Combinations of intelligent and conventional techniques are commonly used the control of complex dynamic systems. Such hybrid schemes have proved to be efficient and can overcome the deficiencies of conventional and intelligent controllers alone. The current study is confined to the development of two forms of hybrid control schemes that combine fuzzy control and conventional PID compensator for input tracking performance. The two hybrid control strategies comprising conventional PO control plus PlO compensator and PO-type fuzzy control plus PlO compensator are developed and implemented for set-point tracking control of the vertical movement of the TRMS rig. It is observed that the hybrid control schemes are superior to other feedback control strategies namely, PlO compensator, pure PO-type and PI-type fuzzy controllers in terms of time domain system behaviour. This research also witnesses investigations into the development of an augmented feedforward and feedback control scheme (AFFCS) for the control of rigid body motion and vibration suppression of the TRMS. The main goal of this framework is to satisfy performance objectives in terms of robust command tracking, fast system response and minimum residual vibration. The developed control strategies have been designed and implemented within both simulation and real-time environments of the TRMS rig. The employed control strategies are shown to demonstrate acceptable performances. The obtained results show that much improved tracking is achieved on positive and negative cycles of the reference signal, as compared to that without any control action. The system performance with the feedback controller is significantly improved when the feedforward control component is added. This leads to the conclusion that augmenting feedback control with feedforward method can lead to more practical and accurate control of flexible systems such as the TRMS

Modelling and control of flexible manipulators

Structural flexibility is a characteristic of all robotic systems. Designing a high performance controller for a robot with a certain degree of link flexibility is not an easy task. This requires, not only a sound knowledge of the dynamics of the system to be controlled, but also a good characterization of the friction as well as an appropriate form of friction compensation. The presence of structural Vibrations in the system during and after high speed positioning makes the design of such a controller even more difficult. This thesis presents a method of modelling and controlling a single-link flexible manipulator for high speed precise end-point positioning. Several mathematicalmodels for a flexible robotic system are presented and described together with those for friction in the system. The parameters of the flexible system such as the natural frequencies, damping ratios and the parameters of friction, including Coulomb and Viscous friction coefficients, are identified offline, based on experimental data. Methods used for finding these parameters are described in detail. The objective of the control system is to move the flexible robot as fast as possible without producing vibrations at the end-point of the move. The position control of a single-link flexible robot is seen as a combination of two different problems namely trajectory planning and trajectory following. Two computational techniques, based on radial basis functions and the assumed-modes method, for planning the trajectories for a single-link flexible robot arm, are presented. These two techniques are compared with the aid of some numerical examples. In order to follow the derived trajectories, a combination of feedback and feedforward control along with a lead compensator is developed. The parameters of the compensator are found using an optimization process based on GeneticAlgorithms. Results of the experiments performed to verify the effectiveness of the proposed control strategy show that feedback control with feedforward compensation is more suitable than a simple feedback controller. Furthermore, these experiments also demonstrate the effectiveness of the trajectory planning process

A comprehensive study of robot control algorithms

The PUMA 560 Industrial Manipulator is presently controlled using a PID control strategy Robot manipulators are highly coupled, nonlinear mechanical systems designed to perform specific tasks. It is the function of any control algorithm to compute the input voltages or torques needed to follow a desired trajectory. The PID controller is detuned, so as to cater for variations in system behaviour. Thus, the performance of such a control algorithm is poor over the entire operating range of the robot and the need for more complex control strategies is clear. The research presented m this thesis derives a third order comprehensive dynamic model for the three primary robot joints, using the Euler-Lagrange formulation for the equations of motion. A simulation package is designed to model this dynamic system. Next, a wide range of different techniques are investigated in a simulation environment, to observe their performance on the computer model. These control algorithms range from Fixed Parameter techniques to Adaptive strategies and Feedforward routines. A set of performance criteria can be used to evaluate these techniques, and the best algonthm from each section is chosen. Using the results of an identification performed on the robot, each of these control methods is applied to the resulting tune varying model. The results here are used to determine the optimal control strategy for manipulator use. Also in this thesis, a new hardware structure is designed and implemented. This structure is capable of implementing complex control routines with adequately low sample periods. The design uses advanced digital signal processors, which can perform arithmetic operations quickly