Brachiating power line inspection robot: controller design and implementation

The prevalence of electrical transmission networks has led to an increase in productivity and prosperity. In 2014, estimates showed that the global electric power transmission network consisted of 5.5 million circuit kilometres (Ckm) of high-voltage transmission lines with a combined capacity of 17 million mega-volt ampere. The vastness of the global transmission grid presents a significant problem for infrastructure maintenance. The high maintenance costs, coupled with challenging terrain, provide an opportunity for autonomous inspection robots. The Brachiating Power Line Inspection Robot (BPLIR) with wheels [73] is a transmission line inspection robot. The BPLIR is the focus of this research and this dissertation tackles the problem of state estimation, adaptive trajectory generation and robust control for the BPLIR. A kinematics-based Kalman Filter state estimator was designed and implemented to determine the full system state. Instrumentation used for measurement consisted of 2 Inertial Measurement Units (IMUs). The advantages of utilising IMUs is that they are less susceptible to drift, have no moving parts and are not prone to misalignment errors. The use of IMU's in the design meant that absolute angles (link angles measured with respect to earth) could be estimated, enabling the BPLIR to navigate inclined slopes. Quantitative Feedback Control theory was employed to address the issue of parameter uncertainty during operation. The operating environment of the BPLIR requires it to be robust to environmental factors such as wind disturbance and uncertainty in joint friction over time. The resulting robust control system was able to compensate for uncertain system parameters and reject disturbances in simulation. An online trajectory generator (OTG), inspired by Raibert-style reverse-time symmetry[10], fed into the control system to drive the end effector to the power line by employing brachiation. The OTG produced two trajectories; one of which was reverse time symmetrical and; another which minimised the perpendicular distance between the end gripper and the power line. Linear interpolation between the two trajectories ensured a smooth bump-less trajectory for the BPLIR to follow

Advanced Motor Control for Improving the Trajectory Tracking Accuracy of a Low-Cost Mobile Robot

This research was funded by the Grant PID2019-111278RB-C21 funded by MCIN/AEI/ 10.13039/501100011033 and “ERDF A way of making Europe”.Peer reviewedPublisher PD

A Unified Anti-Windup Technique for Fuzzy and Sliding Mode Controllers

This paper proposes the unified treatment of an anti-windup technique for fuzzy and sliding mode controllers. A back-calculation and tracking anti-windup scheme is proposed in order to prevent the zero error integrator wind-up in the structures of state feedback fuzzy controllers and sliding mode controllers. The state feedback sliding mode controllers are based on the state feedback-based computation of the switching variable. An example that copes with the position control of an electro-hydraulic servo-system is presented. The conclusions are pointed out on the basis of digital simulation results for the state feedback fuzzy controller

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

Decoupled integral lqr controller with anti-windup compensator for MIMO two rotor aerodynamical system (TRAS)

This paper employs a design of two sub-controllers based on a Linear Quadratic Regulator (LQR) for Two Rotor Aero-dynamical System (TRAS) in two Degree of Freedom (2-DOF) motion. TRAS is a nonlinear Multi-Input Multi-Output (MIMO) system that resembles the behaviour of a helicopter in certain aspects. The main focus of the research work is to control and stabilize the TRAS system in 2-DOF so that the desired trajectory is tracked quickly and accurately even in the presence of disturbances. However, this not always possible due to some reasons such as the strong cross couplings, poorly tuned control parameters and integral windup phenomena that significantly deteriorate the transient response. In this work, TRAS is decoupled into two subsystems (horizontal and vertical) with the cross couplings considered as disturbances. The derivation of the linear model of each subsystem is developed using Jacobean linearisation matrix. An optimal LQR controller is designed and tuned using Particle Swarm Optimisation (PSO) algorithm for each subsystem. To get full state information, provide asymptotic tracking for the reference signal and alleviate integral windup phenomena each sub-LQR controller has been combined with full state observer, integral action gain and anti-windup compensator based on back-calculation technique, respectively to ensure fast and reliable control of TRAS system without degrading the transient response. Experimental results show that the Decoupled Integral LQR Controller (DILQRC) exhibits a better performance in terms of transient and steady state responses with significant reduction of settling time, overshoot percentage and error index it also produces less aggressive and smooth control signals as compared to the Cross Coupled PID Controller (CCPIDC) tuned by the manufacturer

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences