Active Force Control Strategy Research Articles

A novel inertia moment estimation algorithm collaborated with Active Force Control scheme for wheeled mobile robot control in constrained environments

This paper presents a novel inertia moment estimation algorithm to enable the Active Force Control Scheme for tracking a wheeled mobile robot (WMR) effectively in a specific trajectory within constrained environments such as on roads or in factories. This algorithm, also known as laser simulator logic, has the capability to estimate the inertia moment of the AFC-controller when the robot is moving in a pre-planned path with the presence of noisy measurements. The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. A new Proportional-Derivative Active Force Controller (PD-AFC-LS-QC), employing the use of laser simulator logic and quick compensation loop, has been developed in this paper to robustly reject the noise and disturbances. This controller has three feedback control loops, namely, internal, external and quick compensation loops to compensate effectively the disturbances in the constrained environments. A simulation and experimental studies on WMR path control in two kinds of environments; namely, zigzag and highly curved terrains, were conducted to verify the proposed algorithm and controller which was then compared with other existed control schemes. The results of the simulation and experimental works show the capability of the proposed algorithms and the controller to robustly move the WMR in the constrained environments.

An active force controlled of small CMG-based satellite

Purpose This paper aims to investigate the attitude control pointing improvement for a small satellite with control moment gyroscopes (CMGs) using the active force control (AFC) method. Design/methodology/approach The AFC method is developed with its governing equations and integrated into the conventional proportional-derivative (PD) controller of a closed-loop satellite attitude control system. Two numerical simulations of an identical attitude control mission namely the PD controller and the PD+AFC controller were carried out using the MATLAB®-SimulinkTM software and their attitude control performances were demonstrated accordingly. Findings Having the PD+AFC controller, the attitude maneuver can be completed within the desired slew rate, which is about 2.14 degree/s and the attitude pointing accuracies for the roll, pitch and yaw angles have improved significantly by more than 85% in comparison with the PD controller alone. Moreover, the implementation of the AFC into the conventional PD controller does not cause significant difference on the physical structure of the four single gimbal CMGs (4-SGCMGs). Practical implications To achieve a precise attitude pointing mission, the AFC method can be applied directly to the existing conventional PD attitude control system of a CMG-based satellite. In this case, the AFC is indeed the backbone for the satellite attitude performance improvement. Originality/value The present study demonstrates that the attitude pointing of a small satellite with CMGs is improved through the implementation of the AFC scheme into the PD controller.

Robust Intelligent Self-Tuning Active Force Control of a Quadrotor With Improved Body Jerk Performance

This work presents an innovative hybrid control scheme for a quadrotor unmanned aerial vehicle (UAV) model to improve the disturbances rejection capability and body jerk performance by utilizing an active force control (AFC)-based robust intelligent control system via a simulation study. The proposed intelligent control approach incorporates a proportional-integral-derivative (PID) and an intelligent active force control (IAFC) element yielding a robust PID-IAFC scheme. A detailed mathematical model of a quadrotor system with six degrees of freedom (DOFs) was first derived using the Newton-Euler method taking into consideration the gyroscopic terms, disturbances, aerodynamics, and friction effects. In the derived model, the PID controller was first designed to stabilize the quadrotor model and achieve the required altitude and attitude motions. In addition, different types of external disturbances in the form of sinusoidal waves and repeated impulses (pulsating) were added. An AFC strategy, known as PID-AFC, was designed and incorporated into the PID controller, and was initially tuned heuristically. Then, an artificial intelligence (AI)-based method employing an iterative learning (IL) algorithm was designed and implemented into the AFC (ILAFC) to estimate the control parameters automatically while on-line. Thereafter, the performance of the ILAFC was compared to the AFC with fuzzy logic (FL) which became known as FLAFC. Also, a self-tuning (ST) PID controller was designed and employed based on the FL method to automatically tune the PID gains based on the prescribed operating and loading conditions. Moreover, a comparative study of the system performance was carried out utilizing the PID, PID-AFC, ILAFC, FLAFC, and ST-FPID-AFC schemes to analyze the system characteristics. Furthermore, the effectiveness of the AFC-based intelligent controller was investigated in connection with the body jerk performance in the presence of external disturbances. The simulated results reveal the effectiveness and robustness of the proposed control strategy based on the IAFC technique in improving the disturbance rejection capability and body jerk performance by 17% in the presence of uncertainties and external disturbances.

Modelling and control of a Magneto-Rheological elastomer for impact reduction

This article presents the simulation analysis on the effectiveness of impact reduction control based magneto-rheological elastomer isolator device (MREID). The MREID is one of the impact isolator devices that produce controllable stiffness by controlling the input current supply to the device coil. In order to control the input current for MREID, a hybrid control structure combining the skyhook and active force control strategy (HYSAFC) is proposed. Firstly, the characteristics of MREID in squeeze mode are investigated systematically in order to establish the relationship between the supply input current to the subsequent force and impact energy within the MREID. The proposed control strategy is used for force tracking control in determining the amount of input current to be applied to the MREID. The desired input current is determined by a current generator that is developed using inverse ANFIS technique which will regulate the current amount based on the desired force and impact energy. The effectiveness of the actively controlled MREID is evaluated using MATLAB simulations by comparing the performance of the MREID controlled by skyhook control against a passive damper. It is shows that the proposed controller recorded better response compared to skyhook controller, thus improving the stability and the effectiveness in controlling the MRE isolator device.

A simulation and experimental study on wheeled mobile robot path control in road roundabout environment

A robust control algorithm for tracking a wheeled mobile robot navigating in a pre-planned path while passing through the road’s roundabout environment is presented in this article. The proposed control algorithm is derived from both the kinematic and dynamic modelling of a non-holonomic wheeled mobile robot that is driven by a differential drive system. The road’s roundabout is represented in a grid map and the path of the mobile robot is determined using a novel approach, the so-called laser simulator technique within the roundabout environment according to the respective road rules. The main control scheme is experimented in both simulation and experimental study using the resolved-acceleration control and active force control strategy to enable the robot to strictly follow the predefined path in the presence of disturbances. A fusion of the resolved-acceleration control–active force control controller with Kalman Filter has been used empirically in real time to control the wheeled mobile robot in the road’s roundabout setting with the specific purpose of eliminating the noises. Both the simulation and the experimental results show the capability of the proposed controller to track the robot in the predefined path robustly and cancel the effect of the disturbances.

Design and Experimental Research of Movable Cable-Driven Lower Limb Rehabilitation Robot

Aiming at solving the problems of the existing lower limb rehabilitation robots on aspects of configuration limitations, human–machine compatibility, gravity compensation, and multimodal rehabilitation, a movable cable-driven lower limb rehabilitation robot (MCLR) is proposed in this paper, which can realize the gait training and walking training in passive mode, initiative mode, and assistive mode. First, the structure and working principle of MCLR is introduced. The traction type is further optimized. Second, the key control problems of the passive force servo system are analyzed in detail. In order to improve the loading accuracy and speed during the initiative training, the dynamic model of the cable-driven unit is established. Based on this model, an active force control strategy is proposed. Finally, the speed control strategy and the active force control strategy are studied experimentally. The experimental results show that the speed servo system has good tracking ability, which can meet the requirements of the passive rehabilitation. The active force control strategy can significantly improve the loading accuracy and the dynamic performance of the force servo system. The force servo system has good tracking ability in the normal rehabilitation frequency band, which can meet the requirements of the initiative rehabilitation.

PD CONTROL WITH DESIRED GRAVITY COMPENSATION FOR A NOVEL DYNAMIC BRACE

A novel dynamic brace for the treatment of idiopathic scoliosis based on parallel-actuated robotic system is proposed in this paper. The new brace can apply corrective forces on patients’ spine actively to correct the abnormal spine. However, the gravity of the dynamic system results in some adverse impacts, such as reducing comfort degree of patients, accuracy loss of rehabilitation force control, big error in direction and value of force. To overcome this problem, a new active force control strategy, proportional-derivative (PD) control with desired-gravity-compensation (DGC), is proposed to improve the effectiveness of scoliosis rehabilitation. Considering the electrically driven system and the environment contacting with the brace, the dynamic model of the active brace system is derived using Kane method. Based on the above mentioned, the force controller with DGC is designed for the brace system to compensate the impact of system gravity. The brace experiment system is built and various experiment tests are performed to verify the proposed control strategy. Experiment results demonstrate that the proposed control strategy, PD control with DGC, can distinctly reduce the influence of the brace system gravity and has more efficient control effectiveness compared with the classical PID controller.

Design and implementation of a novel modal space active force control concept for spatial multi-DOF parallel robotic manipulators actuated by electrical actuators

Robotic spine brace based on parallel-actuated robotic system is a new device for treatment and sensing of scoliosis, however, the strong dynamic coupling and anisotropy problem of parallel manipulators result in accuracy loss of rehabilitation force control, including big error in direction and value of force. A novel active force control strategy named modal space force control is proposed to solve these problems.Considering the electrical driven system and contact environment, the mathematical model of spatial parallel manipulator is built. The strong dynamic coupling problem in force field is described via experiments as well as the anisotropy problem of work space of parallel manipulators. The effects of dynamic coupling on control design and performances are discussed, and the influences of anisotropy on accuracy are also addressed. With mass/inertia matrix and stiffness matrix of parallel manipulators, a modal matrix can be calculated by using eigenvalue decomposition. Making use of the orthogonality of modal matrix with mass matrix of parallel manipulators, the strong coupled dynamic equations expressed in work space or joint space of parallel manipulator may be transformed into decoupled equations formulated in modal space. According to this property, each force control channel is independent of others in the modal space, thus we proposed modal space force control concept which means the force controller is designed in modal space. A modal space active force control is designed and implemented with only a simple PID controller employed as exampled control method to show the differences, uniqueness, and benefits of modal space force control. Simulation and experimental results show that the proposed modal space force control concept can effectively overcome the effects of the strong dynamic coupling and anisotropy problem in the physical space, and modal space force control is thus a very useful control framework, which is better than the current joint space control and work space control.

A hybrid active force control of a lower limb exoskeleton for gait rehabilitation.

Owing to the increasing demand for rehabilitation services, robotics have been engaged in addressing the drawbacks of conventional rehabilitation therapy. This paper focuses on the modelling and control of a three-link lower limb exoskeleton for gait rehabilitation that is restricted to the sagittal plane. The exoskeleton that is modelled together with a human lower limb model is subjected to a number of excitations at its joints while performing a joint space trajectory tracking, to investigate the effectiveness of the proposed controller in compensating disturbances. A particle swarm optimised active force control strategy is proposed to facilitate disturbance rejection of a conventional proportional-derivative (PD) control algorithm. The simulation study provides considerable insight into the robustness of the proposed method in attenuating the disturbance effect as compared to the conventional PD counterpart without compromising its tracking performance. The findings from the study further suggest its potential employment on a lower limb exoskeleton.

REAL-TIME IMPLEMENTATION OF FEED RATE ACTIVE FORCE CONTROL OF A SYRINGE FLUID DISPENSER

For precise application, it is imperative to provide accurate and stable performance. The feed flow rate of a syringe fluid dispensing system is regulated through a Proportional- Integral-Derivative (PID) and Active Force Control (AFC) control scheme that was actuated using a DC servo motor considering a real-time implementation. The focus of this study is to control the speed of a DC motor by implementing an AFC strategy in rejecting the disturbance in the system. The AFC is implemented by cascading its control loop with the outer PID controller loop to form a two degree-of-freedom (DOF) controller. The performance of the proposed PID with AFC control scheme was investigated considering both the theoretical simulation and experimental works. The simulation was performed in MATLAB/Simulink computing platform while the real-time experimentation was done by utilising the Arduino MEGA 2560 microcontroller with MATLAB/Simulink driver for the data acquisition, interface and control implementation. The results implies the robustness of the AFC-based system in controlling the feed flow rate of the fluid in the dispenser. The best performance is obtained for 100% AFC with the disturbance due to vibration almost completely compensated via the proposed scheme in comparison to the PID counterpart.

The Control of a Lower Limb Exoskeleton for Gait Rehabilitation: A Hybrid Active Force Control Approach

This paper focuses on the modelling and control of a three-link lower limb exoskeleton for gait rehabilitation. The exoskeleton that is restricted to the sagittal plane is modelled together with a human lower limb model. In this case study, a harmonic disturbance is excited at the joints of the exoskeleton whilst it is carrying out a joint space trajectory tracking. The disturbance is introduced to examine the compensating efficacy of the proposed controller. A particle swarm optimised active force control strategy is proposed to augment the disturbance regulation of a conventional proportional-derivative (PD) control law. The simulation study suggests that the proposed control approach mitigates well the disturbance effect whilst maintaining its tracking performance which is seemingly in stark contrast with its traditional PD counterpart.

Satellite cascade attitude control via fuzzy PD controller with active force control under momentum dumping

In this paper, fuzzy proportional-derivative (PD) controller with active force control (AFC) scheme is studied and employed in the satellite attitude control system equipped with reaction wheels. The momentum dumping is enabled via proportional integral (PI) controller as the system is impractical without momentum dumping control. The attitude controllers are developed together with their governing equations and evaluated through numerical treatment with respect to a reference satellite mission. From the results, it is evident that the three axis attitudes accuracies can be improved up to ±0.001 degree through the fuzzy PD controller with AFC scheme for the attitude control. In addition, the three-axis wheel angular momentums are well maintained during the attitude control tasks.

Active Off-Road Seat Suspension System Using Intelligent Active Force Control

Transmitted vibration from vehicles to driver body generates some problems in the long term. Passive and active seat suspensions are used in heavy duty vehicles to reduce unwanted vibration and prevent health problems due to oscillation. Seat suspension must minimize the driver's body displacement and acceleration to increase riding convenience. Active force control (AFC) method is a new technique which is used in active controllers and makes them more accurate. Therefore, this work represents the possibility of applying AFC strategy for an active seat suspension control to increase its robustness. An AFC-based scheme is designed and simulated in MATLAB software. In addition, artificial neural network (ANN) is integrated into the AFC loop to approximate estimated mass of the seat and human body for the proposed controller. The training of ANN with multi-layer feedforward structure is carried out using Levenberg-Marquardt learning algorithm. To evaluate the neuro-AFC control system robustness, the seat is subjected to various types of disturbances. The results of the present study illustrate that the neuro-AFC technique is computationally simple and efficient compared to the classic proportional-integral-derivative (PID) controller in suppressing undesired vibration of heavy duty vehicles' seat. The neuro-AFC scheme is found to demonstrate superior performance for various road profiles compared to pure PID controller, and it can be successfully utilized in heavy duty vehicles such as industrial and agricultural tractors.

Hybrid learning control for improving suppression of hand tremor

Patients with hand tremors may find routine activities such as writing and holding objects affected. In response to this problem, an active control technique has been examined in order to lessen the severity of tremors. In this article, an online method of a hybrid proportional-integral control with active force control strategy for tremor attenuation is presented. An intelligent mechanism using iterative learning control is incorporated into the active force control loop to approximate the estimation mass parameter. Experiments were conducted on a dummy hand model placed horizontally in a tremor test rig. When activated by a shaker in the vertical direction, this resembles a postural tremor condition. In the proportional-integral plus active force control, a linear voice coil actuator is used as the main active tremor suppressive element. A sensitivity analysis is presented to investigate the robustness of the proposed controller in a real-time control environment. The findings of this study demonstrate that the intelligent active force control and iterative learning controller show excellent performance in reducing tremor error compared to classic pure proportional, proportional-integral and hybrid proportional-integral plus active force control controllers.

A Fuzzy-Active Force Control Architecture Based in Characterizing Nonlinear Systems’ Behavior

This paper presents Active Force Control (AFC) based architecture in characterizing the twin rotor multi-input multi-output (MIMO) system (TRMS). The proposed architecture is expected to produce an optimum control gains in both pitch and yaw responses by introducing decoupling function between pitch and yaw responses. The internal change corresponds to coupling effects, gust and wind turbulence are very difficult to compensate by the classical PID control, but both of them are stamped out as AFC scheme is implemented into the control strategy. The performance of TRMS is further optimized by the realization of hybrid strategy in which an artificial intelligence Fuzzy Logic is integrated into the control architecture.

English

This paper presents a study of vibration control through an active force control (AFC) scheme. AFCs are used widely in dynamic system control and are highly robust control schemes, although under unknown disturbances and operation conditions. In this study, the AFC was incorporated with a conventional proportional-integral-derivative (PID) controller to control an active vibration isolation system. A cutting tool of a turning machine with two degrees of freedom is used in this study. A harmonic force due to an unbalanced rotating mass and a sinusoidal response that represented an internal disturbance were applied to both axes (X and Y) of the models, respectively. Generally, the estimated mass (EM) is the most significant parameter in an AFC scheme; thus, the interest in this study was to obtain the EM via a conventional crude approximation method and an intelligent fuzzy logic method. A new AFC scheme with fuzzy logic control (FLC) was proposed (AFCFLC), which is an AFC combined with a PID and FLC. The main purpose of this scheme was to obtain the optimum EM value via the intelligent method and to suppress vibration. Finally, a demonstration of a comparison study between each control scheme was carried out, which revealed clearly that the proposed AFCFLC scheme was the most superior control method for vibration isolation in both axes of the cutting tool models.

Performance Analysis of the Computed Torque Based Active Force Control for a Planar Parallel Manipulator

This paper presents a novel approach to control a 3-RRR (revolute-revolute-revolute) planar parallel manipulator applying an active force control (AFC) strategy. A PID-based computed torque controller (CTC) was first designed and developed to demonstrate the basic and stable response of the manipulator in order to follow a prescribed trajectory. Then, the AFC part was incorporated into the control scheme in series with the CTC (AFC-CTC) in a cascade form. Performance of the system was demonstrated by the computer simulation results. By using the AFC method, the design of trajectory tracking controller can be conducted based on a precise model of the system. The overall tracking performance was improved with using AFC scheme in presence of known or unknown disturbances. Results clearly illustrate the robustness and effectiveness of the proposed AFC-based scheme as a robust disturbance rejecter compared to the conventional CT controller.

Modelling and control of a human-like arm incorporating muscle models

This article focuses on the modelling and control of a two-link planar mechanical manipulator that emulates a human arm. The simplicity of the control algorithm and its ease of computation are particularly highlighted in this study. The arm is subjected to a vibratory excitation at a specific location on the arm while performing trajectory tracking tasks in two-dimensional space, taking into account the presence of ‘muscle’ elements that are mathematically modelled. A closed-loop control system is applied using an active force control strategy to accommodate the disturbances based on a predefined set of loading and operating conditions to observe the system responses. Results of the study imply the effectiveness of the proposed method in compensating the vibration effect to produce robust and accurate tracking performance of the system. The results may serve as a useful tool in aiding the design and development of a tooling device for use in a mechatronic robot arm or even human arm (smart glove) where precise and/or robust performance is a critical factor and of considerable importance.

Implementation of Evolutionary Active Force Control in a 5-Link Biped Robot

In this paper, the application of Active Force Control (AFC) incorporated with a conventional Proportional-Derivative (PD) controller to a five-link biped robot has been studied and simulated. The efficacy and robustness of the AFC strategy in suppressing external disturbances was examined on a model using Crude Approximation (CA) method. However, the task of tuning the PD controller parameters and the inertia matrix coefficient is tedious and time-consuming. Thus, an evolutionary strategy -Differential Evolution (DE) has been proposed in order to tune automatically the parameter gains in a systematic approach. The effectiveness of the proposed method is investigated, and it is found that the system is robust and stable even under influence of disturbances.

A Hybrid Intelligent Active Force Controller for Articulated Robot Arms Using Dynamic Structure Neural Network

The key feature of this paper is the application of a robotic control concept – Active Force Control (AFC). In this type of control, the unknown friction effect of the robotic arm may be compensated by the AFC method. AFC involves the direct measurement of the acceleration and force quantities and therefore, the process of estimating the system ‘disturbance’ due to friction becomes instantaneous and purely algebraic. However, the AFC strategy is very practical provided a good estimation of the inertia matrix of articulated robot arm is acquired. A dynamic structure neural network – Growing Multi-experts Network (GMN) is developed to estimate the robot inertia matrix. The growing and pruning mechanism of GMN ensures the optimum size of the network that results in an excellent generalization capability of the network. Active Force Control (AFC) in conjunction with GMN successfully reduces the velocity and position tracking errors in spite of robot joint friction. The embedded GMN is capable of coupling the inertia matrix estimation on-line that clearly enhances the performance of AFC controller. The robustness and effectiveness of the new hybrid neural network-based AFC scheme are demonstrated clearly with regard to two link articulated robot and a simulated two-degree of freedom Puma 560 robot.