Data-based PID control of flexible joint robot using adaptive safe experimentation dynamics algorithm

This paper proposes the data-based PID controller of flexible joint robot based on adaptive safe experimentation dynamics (ASED) algorithm. The ASED algorithm is an enhanced version of SED algorithm where the updated tuning variable is modified to adapt to the change of the objective function. By adopting the adaptive term to the updated equation of SED, it is expected that the convergence accuracy can be further improved. The effectiveness of the ASED algorithm is verified to tune the PID controller of flexible joint robot. In this flexible joint control problem, two PID controllers are utilized to control both rotary angle tracking and vibration of flexible joint robot. The performance of the proposed data-based PID controller is assessed in terms of trajectory tracking of angular motion, vibration reduction and statistical analysis of the pre-defined control objective function. The simulation results showed that the data-based PID controller based on ASED is able to produce better control accuracy than the conventional SED based method

Decentralized sliding mode control for an electrohydraulic robot manipulator

This thesis is concerned with the problems of modelling and controlling of a 3 DOF electrohydraulic robot manipulators. The control of electrohydraulic robot manipulator is challenging due to the dependence of system parameters on variables such as displacement and velocity, on the geometry and inertia of the links, uncertainties associated with gravity, coriolis and centrifugal forces, variations in payload handled by the manipulator, and environmental influences. To overcome these problems, an integrated mathematical model of the 3 DOF electrohydraulic robot manipulators is treated as a large-scale uncertain system models using the known parameters of the robot. Decentralized control concept is used in this study where the uncertain system is treated as large-scale system which composed of a set of interconnected uncertain subsystems. A variable structure control (VSC) strategy is utilized to overcome the inherent high nonlinearity in the system dynamics under decentralized and centralized frameworks. In each of the approach, a variant of the VSC known as the Sliding Mode Control (SMC) is adopted to ensure the stability of the system dynamics during the sliding phase and to render that the system insensitive to the parametric variations and disturbances. The performance and robustness of the proposed controller is evaluated through computer simulation by using Matlab and Simulink. The results proved that the controller has successfully provided the necessary tracking control for the 3 DOF electrohydraulically driven robot manipulator system

Techniques of Anti-sway and Input Tracking Control of a Gantry Crane System

This paper presents investigations into the development of control schemes for anti-swaying and input tracking control of a gantry crane system. A nonlinear overhead gantry crane system is considered and the dynamic model of the system is derived using the Euler-Lagrange formulation. To study the effectiveness ofthecontrollers, initially a collocated PD control is developed for cart position control of gantry crane. This is then extended to incorporate a non-collocated PID and an input shaper control schemes for anti-swaying control of the system. The positive input shapers with the derivative effects are designed based on the properties of the system. Simulation results of the response of the gantry crane with the controllers are presented in time and frequency domains. The performances of the control schemes are examined in terms of level of input tracking capability, swing angle reduction and time response specifications in comparison to the PD control. Finally, a comparative assessment of the control techniques is presented and discussed

Decentralized controllers design for nonlinear uncertain systems with application on robotic systems

This paper presents investigation into the development of decentralized sliding mode control with application to trajectory tracking for hydraulically driven revolute robot manipulators. The control of hydraulically actuated robot manipulator is very challenging due to the highly nonlinearities in its dynamics, uncertainties parameters, and variations on payload. To overcome these problems, an integrated mathematical model of an N degree-of-freedom (dof) hydraulic robot manipulator is treated as a large-scale uncertain system models with bounded uncertainties where the bounds are known. This is then decomposed into interconnected uncertain subsystems in order to apply the decentralized tracking control strategy. Sliding Mode Control (SMC) and Proportional-Integral Sliding Mode Control strategies will be utilized to overcome the inherent nonlinear dynamics under the decentralized frameworks. These approaches were adopted to ensure the stability of the system dynamics during the sliding mode and the insensitivity to the parameter variations and disturbances. The performance and robustness of the controllers were evaluated on a 3 dof hydraulically actuated manipulator through computer simulation. The results prove that the controllers have succeeded in forcing the 3 DOF hydraulic robot manipulators to track the predefined desired trajectory at all time

A Data-driven Sigmoid-based Secretion Rate of Neuroendocrine-PID Control for TRMS System

This paper investigated the implementation of datadriven sigmoid-based secretion rate of neuroendocrine-PID (SbSR-NEPID) within a twin-rotor MIMO system (TRMS), based on the adaptive safe experimentation dynamics (ASED) algorithm. In essence, SbSR-NEPID is developed as a human body-inspired mechanism that promotes accurate and efficient controller structure. The ASED approach was then employed for parameter tuning of the proposed controller, following its role as the data-driven control scheme that tracks error and input control performances. Fundamentally, such game-theoretic approach would seek optimal parameters through random perturbations of several elements from its controller’s parameters. Its application in tracking both performance and computational interval have also gained vast explorations above statistical ground. As such, results obtained from the simulation has demonstrated data-driven SbSR-NEPID control based on the ASED method as a capable approach in tracking the assigned trajectory missions, while yielding exceptional control accuracy beyond the requirement of theoretical assumptions on the plant dynamics

Development of hardware-in-the-loop (HIL) system from control application

Hardware-in-the-loop (HIL) simulation, or HWIL, is a technique that is used in the development and test of complex real-time embedded systems. HIL simulation provides an effective platform by adding the complexity of the plant under control to the test platform

Adaptive sine-cosine algorithms for global optimization

This paper introduces improved versions of a Sine-Cosine algorithm called Adaptive Sine-Cosine algorithms. It is made adaptive through incorporation of a linear and an exponential term with respect to an individual agent’s fitness. Based on the newly introduced formulas, an individual agent moves with a dynamic and different step sizes compared to other agents through the whole searching process. It also introduces a balance exploration and exploitation strategies. The proposed algorithms in comparison to the original algorithm are then tested with several test functions that have different properties and landscapes. The algorithms performance in terms of their achievement of finding a near optimal solution is analyzed and discussed. Numerical result of the test shows that the proposed algorithms have achieved a better accuracy. The finding also shows that the proposed algorithms have attained a faster convergence toward the near optimal solution