Harun Tugal

Bio: Harun Tugal is an academic researcher from Heriot-Watt University. The author has contributed to research in topics: Computer science & Teleoperation. The author has an hindex of 4, co-authored 13 publications receiving 62 citations. Previous affiliations of Harun Tugal include Adana Science and Technology University & Karadeniz Technical University.

Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay

Abstract: In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided.

Stability Analysis of Bilateral Teleoperation With Bounded and Monotone Environments via Zames–Falb Multipliers

Abstract: This paper provides less conservative stability conditions for bilateral teleoperation by exploiting the advantages of the integral quadratic constraint (IQC) framework, where the environment can be defined as a memoryless, bounded, and monotonic nonlinear operator. Recent advances in multiplier theory for appropriate classes of uncertainties/nonlinearities are applied. Since the classes of multipliers have infinite dimension, parametrization of these multipliers is used to obtain convex searches over a finite number of parameters. The stability of the system is analyzed as a Lurye system containing time delay and monotone nonlinearity. As a result, less conservative delay-dependent conditions can be developed. These results are then applied to bilateral teleoperation. Stability results are tested with different experiments, in particular, bilateral teleoperation experiments over the Internet between Manchester, U.K., and Vigo, Spain, have been carried out. The advantage of the proposed approach is demonstrated by reaching higher transparency index for two-channel position–force teleoperation while ensuring absolute stability.

Absolute Stability of Systems With Integrator and/or Time Delay via Off-Axis Circle Criterion

Abstract: Graphical methods are a key tool to analyze Lur’e systems with time delay. In this letter we revisit clockwise properties of the Nyquist plot and extend results in the literature to critically stable systems and time-delayed systems. It is known that rational transfer functions with no resonant poles and no zeros satisfy the Kalman conjecture. We show that the same class of transfer functions in series with a time delay also satisfies the Kalman conjecture. Furthermore the same class of transfer functions in series with an integrator and delay (which may be zero) satisfies a suitably relaxed form of the Kalman conjecture. Useful results are also obtained where the delay is constant but unknown. Results in this letter can be used as benchmarks to test sufficient stability conditions for the Lur’e problem with time-delay systems.

A Robotic Experimental Setup with a Stewart Platform to Emulate Underwater Vehicle-Manipulator Systems

Abstract: This study presents an experimental robotic setup with a Stewart platform and a robot manipulator to emulate an underwater vehicle–manipulator system (UVMS). This hardware-based emulator setup consists of a KUKA IIWA14 robotic manipulator mounted on a parallel manipulator, known as Stewart Platform, and a force/torque sensor attached to the end-effector of the robotic arm interacting with a pipe. In this setup, we use realistic underwater vehicle movements either communicated to a system in real-time through 4G routers or recorded in advance in a water tank environment. In addition, we simulate both the water current impact on vehicle movement and dynamic coupling effects between the vehicle and manipulator in a Gazebo-based software simulator and transfer these to the physical robotic experimental setup. Such a complete setup is useful to study the control techniques to be applied on the underwater robotic systems in a dry lab environment and allows us to carry out fast and numerous experiments, circumventing the difficulties with performing similar experiments and data collection with actual underwater vehicles in water tanks. Exemplary controller development studies are carried out for contact management of the UVMS using the experimental setup.

Teleoperation with memoryless, monotone, and bounded environments: A Zames-Falb multiplier approach

Abstract: Absolute stability of bilateral teleoperation has been investigated under the assumption that both human and environment behave as passive systems. This robust design is required since human and environment must be considered as unknown systems at the design stage. If this approach is widely used in the literature, it leads to conservative conditions. Recently, teleoperation has been described in the integral quadratic constraint (IQC) framework, which provides powerful tools to develop less conservative description of both, human and environment. In this initial work, we consider that the environment can be described by a memoryless, monotone, and bounded nonlinearity. Then, Zames-Falb multipliers can be introduced to relax the conservatism of current state-of-the-art stability conditions. The usefulness of our result is shown in a 2-channel position-force teleoperation; where the well known lack of passivity of a PD-F controller is corrected by the use of Zames-Falb multipliers.

Reinforcement Learning-Based Optimal Tracking Control of an Unknown Unmanned Surface Vehicle

Abstract: In this article, a novel reinforcement learning-based optimal tracking control (RLOTC) scheme is established for an unmanned surface vehicle (USV) in the presence of complex unknowns, including dead-zone input nonlinearities, system dynamics, and disturbances. To be specific, dead-zone nonlinearities are decoupled to be input-dependent sloped controls and unknown biases that are encapsulated into lumped unknowns within tracking error dynamics. Neural network (NN) approximators are further deployed to adaptively identify complex unknowns and facilitate a Hamilton–Jacobi–Bellman (HJB) equation that formulates optimal tracking. In order to derive a practically optimal solution, an actor–critic reinforcement learning framework is built by employing adaptive NN identifiers to recursively approximate the total optimal policy and cost function. Eventually, theoretical analysis shows that the entire RLOTC scheme can render tracking errors that converge to an arbitrarily small neighborhood of the origin, subject to optimal cost. Simulation results and comprehensive comparisons on a prototype USV demonstrate remarkable effectiveness and superiority.

Asymmetrical interval type-2 fuzzy logic control based MPPT tuning for PV system under partial shading condition

Abstract: The conventional maximum power point tracking (MPPT) algorithm shows best performance under uniform insolation but when photovoltaic (PV) array is partially irradiated, the Power vs Voltage (P–V) plot consists of multiple local maxima power point (LMPP) and one global maxima power point (GMPP). The conventional MPPT algorithm may track local peak and fluctuate around it, resulting in lower power tracking. To eradicate this drawback of conventional algorithm, the solar PV system requires the synthesis of modified controller which is able to discriminate between local and global peak point. Along with implementing modified MPPT controller, to minimise the adverse effect of partial shading on PV system, different PV array arrangements like series-parallel (SP), honey comb (HC), total cross tied (TCT) etc. may be used. Author(s) in the present study, has proposed asymmetrical interval type-2 fuzzy logic control (IT-2 AFLC) based MPP algorithm for tracking global peak in partial shading condition (PSC) with different PV array arrangements. The presented algorithm has been compared with other approaches viz. perturb & observe (P&O) and type-1(T-1) FLC for GMPP tracking, fill factor, shading losses, mismatch loss and efficiency to establish its superiority. For evaluating the efficiency of different algorithms, the EN50530 MPPT efficiency test has been performed under dynamic condition. The proposed algorithm has been developed under MATLAB/Simulink environment.

Robust Formation Control for Cooperative Underactuated Quadrotors via Reinforcement Learning

Abstract: In this article, the model-free robust formation control problem is addressed for cooperative underactuated quadrotors involving unknown nonlinear dynamics and disturbances. Based on the hierarchical control scheme and the reinforcement learning theory, a robust controller is proposed without knowledge of each quadrotor dynamics, consisting of a distributed observer to estimate the position state of the leader, a position controller to achieve the desired formation, and an attitude controller to control the rotational motion. Simulation results on the multiquadrotor system confirm the effectiveness of the proposed model-free robust formation control method.