Nonlinear control for Two-Link flexible manipulator

Recently the use of robot manipulators has been increasing in many applications such as medical applications, automobile, construction, manufacturing, military, space, etc. However, current rigid manipulators have high inertia and use actuators with large energy consumption. Moreover, rigid manipulators are slow and have low payload-to arm-mass ratios because link deformation is not allowed. The main advantages of flexible manipulators over rigid manipulators are light in weight, higher speed of operation, larger workspace, smaller actuator, lower energy consumption and lower cost. However, there is no adequate closed-form solutions exist for flexible manipulators. This is mainly because flexible dynamics are modeled with partial differential equations, which give rise to infinite dimensional dynamical systems that are, in general, not possible to represent exactly or efficiently on a computer which makes modeling a challenging task. In addition, if flexibility nature wasn\u27t considered, there will be calculation errors in the calculated torque requirement for the motors and in the calculated position of the end-effecter. As for the control task, it is considered as a complex task since flexible manipulators are non-minimum phase system, under-actuated system and Multi-Input/Multi-Output (MIMO) nonlinear system. This thesis focuses on the development of dynamic formulation model and three control techniques aiming to achieve accurate position control and improving dynamic stability for Two-Link Flexible Manipulators (TLFMs). LQR controller is designed based on the linearized model of the TLFM; however, it is applied on both linearized and nonlinear models. In addition to LQR, Backstepping and Sliding mode controllers are designed as nonlinear control approaches and applied on both the nonlinear model of the TLFM and the physical system. The three developed control techniques are tested through simulation based on the developed dynamic formulation model using MATLAB/SIMULINK. Stability and performance analysis were conducted and tuned to obtain the best results. Then, the performance and stability results obtained through simulation are compared. Finally, the developed control techniques were implemented and analyzed on the 2-DOF Serial Flexible Link Robot experimental system from Quanser and the results are illustrated and compared with that obtained through simulation

Tracking control of redundant mobile manipulator: An RNN based metaheuristic approach

In this paper, we propose a topology of Recurrent Neural Network (RNN) based on a metaheuristic optimization algorithm for the tracking control of mobile-manipulator while enforcing nonholonomic constraints. Traditional approaches for tracking control of mobile robots usually require the computation of Jacobian-inverse or linearization of its mathematical model. The proposed algorithm uses a nature-inspired optimization approach to directly solve the nonlinear optimization problem without any further transformation. First, we formulate the tracking control as a constrained optimization problem. The optimization problem is formulated on position-level to avoid the computationally expensive Jacobian-inversion. The nonholonomic limitation is ensured by adding equality constraints to the formulated optimization problem. We then present the Beetle Antennae Olfactory Recurrent Neural Network (BAORNN) algorithm to solve the optimization problem efficiently using very few mathematical operations. We present a theoretical analysis of the proposed algorithm and show that its computational cost is linear with respect to the degree of freedoms (DOFs), i.e., O(m). Additionally, we also prove its stability and convergence. Extensive simulation results are prepared using a simulated model of IIWA14, a 7-DOF industrial-manipulator, mounted on a differentially driven cart. Comparison results with particle swarm optimization (PSO) algorithm are also presented to prove the accuracy and numerical efficiency of the proposed controller. The results demonstrate that the proposed algorithm is several times (around 75 in the worst case) faster in execution as compared to PSO, and suitable for real-time implementation. The tracking results for three different trajectories; circular, rectangular, and rhodonea paths are presented

Modelling and control of a two-link flexible manipulator using finite element modal analysis

This thesis focuses on Finite Element (FE) modeling and robust control of a two-link flexible manipulator based on a high resolution FE model and the system vibration modes. A new FE model is derived using Euler-Bernoulli beam elements, and the model is validated using commercial software Abaqus CAE. The frequency and time domain analysis reveal that the response of the FE model substantially varies with changing the number of elements, unless a high number of elements (100 elements in this work) is used. The gap between the complexity of the high order FE model capable of predicting dynamics of the multibody system, and suitability of the model for controller design is bridged by designing control schemes based on the reduced order models obtained using modal truncation/H8 techniques. Two reduced order multi-input multi-output modal control algorithms composed of a robust feedback controller along with a feed-forward compensator are designed. The first controller, Inversion-based Two Mode Controller (ITMC), is designed using a mixed-sensitivity H8 synthesis and a modal inversion-based compensator. The second controller, Shaping Two-Mode Controller (STMC), is designed with H8 loopshaping using the modal characteristics of the system. Stability robustness against unmodelled dynamics due to the model reduction is shown using the small gain theorem. Performance of the feedback controllers are compared with Linear Quadratic Gaussian designs and are shown to have better tracking characteristics. Effectiveness of the control schemes is shown by simulation of rest-to-rest maneuver of the manipulator to a set of desired points in the joint space. The ITMC is shown to have more precise tracking performance, while STMC has higher control over vibration of the tip, at the expense of more tracking errors

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Task-space dynamic control of underwater robots

This thesis is concerned with the control aspects for underwater tasks performed by marine robots. The mathematical models of an underwater vehicle and an underwater vehicle with an onboard manipulator are discussed together with their associated properties. The task-space regulation problem for an underwater vehicle is addressed where the desired target is commonly specified as a point. A new control technique is proposed where the multiple targets are defined as sub-regions. A fuzzy technique is used to handle these multiple sub-region criteria effectively. Due to the unknown gravitational and buoyancy forces, an adaptive term is adopted in the proposed controller. An extension to a region boundary-based control law is then proposed for an underwater vehicle to illustrate the flexibility of the region reaching concept. In this novel controller, a desired target is defined as a boundary instead of a point or region. For a mapping of the uncertain restoring forces, a least-squares estimation algorithm and the inverse Jacobian matrix are utilised in the adaptive control law. To realise a new tracking control concept for a kinematically redundant robot, subregion tracking control schemes with a sub-tasks objective are developed for a UVMS. In this concept, the desired objective is specified as a moving sub-region instead of a trajectory. In addition, due to the system being kinematically redundant, the controller also enables the use of self-motion of the system to perform sub-tasks (drag minimisation, obstacle avoidance, manipulability and avoidance of mechanical joint limits)

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