Abdul Rashid Husain

System identification of electro-hydraulic actuator servo system

This paper presents the system identification process done on an industrial Electro-Hydraulic Actuator (EHA) system. The model obtained through system identification by aid of System Identification Toolbox of MATLAB and System Identification Toolkit of LabVIEW. Attraction of system identification is ability to obtain systems model with sets of input and output data; without need of prior knowledge on system. The model is later validated with the actual performance of real EHA system.

Modeling and controller design of an industrial hydraulic actuator system in the presence of friction and internal leakage

This paper presents a robust controller scheme and its capabilities to control the position tracking performance of an electro-hydraulic actuator system. Sliding mode control with fixed and varying boundary layer is proposed in the scheme. It is aimed to compensate nonlinearities and uncertainties caused by the presence of friction and internal leakage. Its capabilities are verified through simulations in Matlab Simulink environment. The friction was represented by the LuGre model and the internal leakage was assumed to change. The results indicate that the scheme successfully improves the robustness and the tracking accuracy of the system. This improvement offers a significant contribution in the control of modern equipment positioning applications.

A Particle Swarm Optimization Approach to Robotic Drill Route Optimization

Most of the operational time of a PCB Robotic Drill is spent on moving the drill bit between the holes. This operational time can be kept at a minimal level by optimizing the route taken by the robot. An optimized route translates to a minimal cost of operating the robot. This paper proposes a new model that implements Particle Swarm Optimization (PSO) in order to find optimized routing path when using the PCB Robotic Drill. The main task of the PCB Robotic Drill is to drill holes at Printed Circuit Board (PCB). This PCB Robotic Drill will route the drill site by moving the drill bit along Cartesian axes from it’s initial position. Then, the drill bit will return back to the initial position. The drill route consists of a number of potential locations where the holes are going to be drilled. As the number of holes required increases so thus does the complexity to find the optimized route. The proposed model can be used to solve this complex problem with minimal computational time. The result of a case study indicates that the proposed model is capable to find the shortest path for the robot to complete its task. Thus concluded the proposed model can be implemented in any drill route problems.

Enhanced Backstepping Controller Design with Application to Autonomous Quadrotor Unmanned Aerial Vehicle

Quadrotor unmanned aerial vehicle (UAV) is an underactuated multi-input and multi-output (MIMO) system which has nonlinear dynamic behavior such as high coupling degree and unknown nonlinearities. It is a great challenge to design a quadrotor control system due to these features. In this paper, the contribution is focused on the backstepping-based robust control design of the quadrotor UAV. Firstly, the dynamic model of the aerial vehicle is mathematically formulated. Then, a robust controller is designed for the stabilization and tracking control of the vehicle. The developed robust control system comprises a backstepping and a proportional-derivative (PD) controller. Backstepping is a recursive design methodology that uses Lyapunov theorem which can guarantee the stability of the nominal model system, while PD control is used to attenuate the effects caused by system uncertainties. For the problem of determining the backstepping control parameters, particle swarm optimization (PSO) algorithm has been employed. In addition, the genetic algorithm (GA) technique is also adopted for the purpose of performance comparison with PSO scheme. Finally, the designed controller is experimentally evaluated on a quadrotor simulation environment to demonstrate the effectiveness and merits of the theoretical development.

Intelligent adaptive backstepping control for MIMO uncertain non-linear quadrotor helicopter systems

Designing a controller for multi-input–multi-output (MIMO) uncertain non-linear systems is one of the most important challenging works. In this paper, the contribution is focused on the design and analysis of an intelligent adaptive backstepping control for a MIMO quadrotor helicopter perturbed by unknown parameter uncertainties and external disturbances. The design approach is based on the backstepping technique and uses a radial basis function neural network (RBFNN) as a perturbation approximator. First, a backstepping controller optimized by the particle swarm optimization is developed for a nominal helicopter dynamic model. Then, the unknown perturbations are approximated based on the universal approximation property of the RBFNN. The parameters of the RBFNN are adjusted through online learning. To improve the control design performance further, a fuzzy compensator is introduced to eliminate the approximation error produced by the neural approximator. Asymptotical stability of the closed-loop control system is analytically proven via the Lyapunov theorem. The main advantage of the proposed methodology is that no prior knowledge of parameter uncertainties and disturbances is required. Simulations of hovering and trajectory tracking missions of a quadrotor helicopter are conducted. The results demonstrate the effectiveness and feasibility of the proposed approach.

Linear matrix inequality-based robust proportional derivative control of a two-link flexible manipulator

This paper presents the design and development of a robust proportional derivative (PD) controller based on linear matrix inequality (LMI) for the control of a hub angular position and end-point deflection of a planar two-link flexible manipulator. The dynamics of the manipulator is uncertain and time varying due to the variation of payloads that result in large variations in the excitation of flexible modes. Practical design steps are presented in which the LMI-based conditions are formulated to obtain a robust PD gains to control the flexible manipulator. The robust controller has an advantage as compared to the Ziegler-Nichols tuned PD controller as the identified PD gains can be used to control the system under various loading conditions. The performances of the proposed controller are evaluated in terms of input tracking capability of the hub angular position response and level of deflection of both links of the flexible manipulator. Experimental results show that despite using the same sets of PD gains, LMI-PD control provides better robustness and system performance.

Switching between formations for multiple mobile robots via synchronous controller

This paper proposes a new synchronous control law to perform multiple mobile robots trajectory tracking while maintaining time-varying formations. Each robot is controlled to track its desired trajectory while synchronizing its motion with the two nearby robots to maintain the desired time-varying formation. The dynamic model of the wheeled mobile robot (WMR) is derived, so as, it can be divided into a translational and rotational model, in order to control each model separately. Then, a synchronous controller for each robots translation is proposed to guarantee the asymptotic stability of both position and synchronization errors. Also, an orientation controller is proposed to ensure that the robot is always oriented towards its desired position. The simulation results verify the effectiveness of the proposed synchronous controller in the formation control tasks.

Dynamic modelling and characterisation of a two-link flexible robot manipulator

This paper presents an investigation into the dynamic modelling and characterisation of a two-link flexible robot manipulator. A planar two-link flexible manipulator incorporating structural damping, hub inertia and payload that moves in the horizontal plane is considered. A dynamic model of the system is developed using a combined Euler-Lagrange and assumed mode method. Simulation is performed to assess the dynamic model and system responses at the hub and end-point of both links are presented and analysed in time and frequency domains. Moreover, effects of payload on the dynamic characteristics of the flexible manipulator are studied and discussed.

System identification and control of an Electro-Hydraulic Actuator system

Precise control of Electro-Hydraulic Actuator (EHA) system has been a challenging task due to nonlinearities, time varying characteristics and uncertainties of the system. A controller can be designed when given accurate model of the system. This paper presents the process to obtain an EHA systems model using system identification approach. System identification process has merit in obtaining system model as it requires only input and output data pairs from the system. Validation of the model is done by comparing the performance with the actual EHA system. A PID controller is later designed based on model obtained for accurate position tracking of the system. Simulation result and real time experiment show that the system which is applied with the proposed controller is able to perform position tracking with high accuracy.

A new error handling algorithm for controller area network in networked control system

An effective error handling mechanism plays an important role to ensure the reliability and robustness of the application of controller area network (CAN) in controlling dynamic systems. This paper addresses a new online error handling approach or named per-sample-error-counting (PSeC) technique that tends to replace native error handling protocol in controller area network (CAN). The mechanism is designed to manage transmission errors of both sensor and control data in networked control system (NCS) used in controlling dynamic system such that the stability of the feedback system is preserved. A new parameter denoted as maximum allowable number of error burst (MAEB) is introduced in which MAEB is selected based on available bandwidth of the CAN network. MAEB serves as the maximum number of attempt of re-transmission of erroneous data per sample which allows the maximum transmission period to be known and guaranteed for time-critical control system. The efficacy of the proposed method is verified by applying the algorithm on the fourth order inverted pendulum system simulated on Matlab/Truetime simulator and the performance is benchmarked with the existing CAN error management protocol. The simulation run under various systems conditions demonstrate that the proposed method results in superior system performance in handling data transmission error as well as meeting control system requirement.