PD Control Scheme Research Articles

Design and Force/Angle Independent Control of a Bionic Mechanical Ankle Based on an Artificial Muscle Matrix.

Inspired by the natural skeletal muscles, this paper presents a novel shape memory alloy-based artificial muscle matrix (AMM) with advantages of a large output force and displacement, flexibility, and compactness. According to the composition of the AMM, we propose a matrix control strategy to achieve independent control of the output force and displacement of the AMM. Based on the kinematics simulation and experiments, we obtained the output displacement and bearing capacity of the smart digital structure (SDS) and confirmed the effectiveness of the matrix control strategy to achieve force and displacement output independently and controllably. A bionic mechanical ankle actuated by AMM was proposed to demonstrate the actuating capability of the AMM. Experimental results show that the angle and force of the bionic mechanical ankle are output independently and have a significant gradient. In addition, by using a self-sensing method (resistance self-feedback) and PD control strategy, the output angle and force of the bionic mechanical ankle can be maintained for a long time without overheating of the AMM.

Commuted PD Controller for Nonlinear Systems: Glucose–Insulin Regulatory Case

As an option to deal with insulin-dependent disease, a recently commuted PD control strategy is designed and carefully analyzed for different clinic diabetic patients. This controller approach is mainly conceived to stabilize the glucose blood concentration in a diabetic patient around its basal value; hence, avoiding extreme situations such as hypoglycemia and hyperglycemia. This control strategy receives two inputs carefully tuned to actuate when the measured variable is out of a prescribed healthy zone. Therefore, one of these variables is invoked to decrease the glucose concentration to insulin injection, and the other is employed to increase the glucose absorption, both by using a proper PD controller. According to our numerical experiments, our controller approach performs well, even when there is an external disturbance in the controlled system.

Bifurcation control of a fractional-order PD control strategy for a delayed fractional-order prey–predator system

Bifurcation control of a fractional-order PD control strategy for a delayed fractional-order prey–predator system

Enhanced extended state observer-based model-free force control for a Series Elastic Actuator

With inherent mechanical compliance and programmable force controllability, the Series Elastic Actuator (SEA) has been a popular choice for modern mechanical systems. It is crucial to realize accurate and robust force control for a SEA, especially in a physical human–robot interaction condition. In this paper, a model-free force controller (MFFC) for the SEA is developed, which relies only on the input–output measurement. Firstly, based on the ultra-local model concept, the SEA force dynamics is reformulated in a simpler way, and all unknown terms are grouped as one term called lumped total disturbance. Secondly, an enhanced extended stated observer (EESO) is designed to simultaneously estimate the lumped total disturbance, the force velocity, and the control input gain. Thirdly, a disturbance rejective intelligent PD (iPD) control scheme is established. In addition, the effects of the control input gain are analyzed and the close-loop stability is demonstrated with Lyapunov method. The control accuracy and robustness of the MFFC are verified in a physical human–robot interaction environment.

Self-Tuning Control of Manipulator Positioning Based on Fuzzy PID and PSO Algorithm.

With the manipulator performs fixed-point tasks, it becomes adversely affected by external disturbances, parameter variations, and random noise. Therefore, it is essential to improve the robust and accuracy of the controller. In this article, a self-tuning particle swarm optimization (PSO) fuzzy PID positioning controller is designed based on fuzzy PID control. The quantization and scaling factors in the fuzzy PID algorithm are optimized by PSO in order to achieve high robustness and high accuracy of the manipulator. First of all, a mathematical model of the manipulator is developed, and the manipulator positioning controller is designed. A PD control strategy with compensation for gravity is used for the positioning control system. Then, the PID controller parameters dynamically are minute-tuned by the fuzzy controller 1. Through a closed-loop control loop to adjust the magnitude of the quantization factors–proportionality factors online. Correction values are outputted by the modified fuzzy controller 2. A quantization factor–proportion factor online self-tuning strategy is achieved to find the optimal parameters for the controller. Finally, the control performance of the improved controller is verified by the simulation environment. The results show that the transient response speed, tracking accuracy, and follower characteristics of the system are significantly improved.

Disturbance observer-based LPV feedback control of a [formula omitted]-DoF robotic manipulator including compliance through gain shifting

This paper proposes a control scheme for a N-DoF robotic manipulator in a joint-regulation motion problem, dealing with disturbances (as e.g. exogenous forces, unmodelled dynamics) that hinder task fulfilment, and also considering that not all the required states are available online. Existing literature tackles this problem through Disturbance Observer (DO) strategies which imply complex analysis and design methods or introducing strong assumptions. Conversely, we propose to formulate the system as a Linear Parameter Varying (LPV) model, which allows a straightforward application of the existing linear control structures but without neglecting its non-linear behaviour. We make use of the Robust Unknown Input Observer (RUIO) to obtain (for not measurable states) a decoupled estimation from the unknown disturbance effects, and improve its noise reduction capabilities through the new optimal RUIO design. The robotic manipulator is controlled with a state-feedback control law that, making use of the LPV paradigm, has been designed to seamlessly avoid torque saturation on manipulator’s joints through a gain shifting strategy that modifies its compliant behaviour. Stability and performance requirements are imposed in both RUIO and state-feedback control synthesis problems stated using the LMI framework, applying Polya’s theorems on positive forms of the standard simplex to reduce its overall conservatism. Experiments, using a simulated head system of the TIAGo robot as a testbed in various realistic scenarios, show the benefits when compared to the existing joint-independent PD control strategy and state-of-art EKF disturbance estimation.

Human-Like Robust Adaptive PD Based Human Gait Tracking for Exoskeleton Robot

For patients with dyskinesias caused by central nervous system diseases such as stroke, in the early stage of rehabilitation training, lower limb rehabilitation robots are used to provide passive rehabilitation training. This paper proposed a human-like robust adaptive PD control strategy of the exoskeleton robot based on healthy human gait data. When the error disturbance is bounded, a human-like robust adaptive PD control strategy is designed, which not only enables the rehabilitation exoskeleton robot to quickly track the human gait trajectory obtained through the 3D NOKOV motion capture system, but also can well identify the structural parameters of the system and avoid excessively initial output torque for the robot. MATLAB simulation verifies that the proposed method has a better performance to realize tracking the experimental trajectory of human movement and anti-interference ability under the condition of ensuring global stability for a lower limb rehabilitation exoskeleton robot.

Adaptive Fuzzy Control for Attitude Stabilization of Spacecraft with Deployable Composite Laminated Solar Array

Modern spacecraft are often equipped with large-scale, complex, and lightweight solar arrays whose deployment involves a highly dynamic movement. This paper proposed a novel adaptive proportional-derivative typed fuzzy logic control scheme for the attitude stabilization of a flexible spacecraft during the deployment of a composite laminated solar array. First, a constrained rigid-flexible coupling spacecraft model consisting of a rigid main body and a flexible solar array was proposed. The solar array, which is composed of composite laminated shells, was described by the absolute nodal coordinate formulation. Then, the detailed derivation of the adaptive fuzzy PD controller for attitude stabilization of the spacecraft was discussed. In addition, the spacecraft dynamic model which integrated the adaptive fuzzy PD controller was derived as a set of differential-algebraic equations. Several simulations were developed to investigate the solar array deployment dynamics and to verify the effectiveness of the proposed adaptive fuzzy PD controller. The results suggested that the proposed dynamic model is able to exactly describe the deployment dynamics of the composite laminated solar array. The solar array deployment causes obvious translational and rotational motions of the spacecraft. The proposed adaptive fuzzy PD control scheme has better performance in terms of the control precision and time response in stabilizing spacecraft during the deployment of the composite laminated solar array, comparing with that of the conventional PD controller.

Levitation Stability and Hopf Bifurcation of EMS Maglev Trains

This paper analyzed the mechanical characteristics of single electromagnet system and elastic track beam of EMS maglev train and established a five-dimensional dynamics model of single electromagnet-track beam coupled system with classical PD control strategy adopted for its levitation system. Then, based on the Hurwitz criterion and the high-dimensional Hopf bifurcation theory, the stability of the coupled system is analyzed; the existence of the Hopf bifurcation is discussed and the bifurcation direction and the stability of the periodic solution are determined with levitation control feedback coefficient kp as the bifurcation parameter; and numerical simulation is conducted to verify the validity of the theoretical analysis results. The results show that the Hurwitz algebra criterion can directly determine the eigenvalues and symbols of the dynamics system to facilitate the analysis on the stability of the system and the Hopf bifurcation without the necessity of calculating the specific eigenvalues; supercritical Hopf bifurcation will occur under the given parameters, that is, when kp<kp0, the real-time system is asymptotically stable, yet Hopf bifurcation occurs as kp increases gradually beyond kp0, with the stability of the system lost and a stable limit cycle branched.

PD Control at the Hopf Bifurcation Point of a Neuron System with Inertia and Delay

In this paper, a two-neuron system with inertia and delay is proposed firstly. a PD controller is then applied to the system for the purpose of improving its dynamical performance. Through the mathematical transformation, we extend the system to a four-dimensional one with only time delays. With the help of the associated characteristic equation of the mathematical model, suffcient conditions for ensuring the system stability are proposed. Furthermore, with the time delay as the bifurcation parameter, relevant requirements for the generation of Hopf bifurcation are derived. Then a series of numerical simulatiosns are carried out to justify the theoretical analysis and it is found that the application of PD control scheme helps to advance the bifurcation point dramatically through a slight adjustment of the controller parameters.

Finite-time Robust Trajectory Tracking Control of Unmanned Underwater Vehicles

In this paper, the finite-time tracking control problem of unmanned underwater vehicle in complex environment is studied. By combining dynamic surface control with second-order sliding mode control, a finite-time dynamic surface sliding mode composite track tracking control scheme is designed. Ensure that the unmanned underwater vehicle track tracking system has high-quality track tracking performance such as fastness, accuracy, strong robustness and limited time convergence. Finally, the simulation experiment and the traditional PD control strategy tracking effect are compared and analyzed to verify the effectiveness and superiority of the proposed track tracking control method.

Adaptive PD Control Based on RBF Neural Network for a Wire-Driven Parallel Robot and Prototype Experiments

An adaptive PD control scheme is proposed for the support system of a wire-driven parallel robot (WDPR) used in a wind tunnel test. The control scheme combines a PD control and an adaptive control based on a radial basis function (RBF) neural network. The PD control is used to track the trajectory of the end effector of the WDPR. The experimental environment, the external disturbances, and other factors result in uncertainties of some parameters for the WDPR; therefore, the RBF neural network control method is used to approximate the parameters. An adaptive control algorithm is developed to reduce the approximation error and improve the robustness and control precision of the WDPR. It is demonstrated that the closed-loop system is stable based on the Lyapunov stability theory. The simulation results show that the proposed control scheme results in a good performance of the WDPR. The experimental results of the prototype experiments show that the WDPR operates on the desired trajectory; the proposed control method is correct and effective, and the experimental error is small and meets the requirements.

Reinforcement Learning Compensation based PD Control for a Double Inverted Pendulum

In this paper, we present a Control Algorithm based on Reinforcement Learning for a double inverted pendulum on a cart. By implementing the Q-Learning techniques in the PD control scheme, the second pendulum (top pendulum) is enabled to improve its performance. In a first step, Q-Learning is used so that the control can balance the second pendulum towards its inverted vertical position, while the first pendulum has no restrictions on its movement and also the car remains in a range of ±1 meter in its displacement. In a second step, we combine hybrid techniques of Q-Learning and PD control, in a system that has had changes in its parameters and in its initial conditions. Then, with the hybrid control, we obtain better results than using the controllers individually. Finally, the simulation results show the effectiveness of the proposed controller.

Three-dimensional dynamic bipedal walking based on passive dynamic walking mechanism using telescopic knee via phase oscillator with ground reaction force

This study aims to generate 3-D dynamic bipedal walking using two oscillators of a CPG approach based on its body dynamics. First, a 3-D biped, which inherited the aspect of the previous passive dynamic walker, was developed that contained flat feet with pressure sensors, ankle joints composed of ball joints surrounded by coil springs, telescopic knees, and actuated hip joints using a direct drive (DD) motor. The torso was controlled by the DD motors using a PD control scheme. Next, the Owaki–Ishiguro method was used with ground contact information in the phase oscillator to the knee joint. Finally, experimental tests were conducted to elucidate the effectiveness of the biped. A 3-D dynamic bipedal gait of RW06 was developed using knee oscillation based on the phase oscillator. Bipedal walking was excited only by the knee oscillation; therefore, the gait was strongly affected by the body dynamics.

Unbounded regulators with variable gains for a direct-drive robot manipulator

This paper addresses the position-control problem with variable gains for robot manipulators. We present a new regulator based on a hyperbolic-sine structure with tuning rules for control gains. It is demonstrated that the equilibrium point of the closed-loop system is globally, asymptotically stable according to Lyapunov theory. By using a similar methodology, this concept can be extended to other unbounded controllers such as PD and PID. In order to show the usefulness of the proposed scheme and with the purpose of validating its asymptotical stability property, an experimental comparison involving constant gains controllers, for example: simple PD, PID and hyperbolic-tangent schemes vs variable-gains hyperbolic-sine and PD control schemes, was performed by using a three degree-of-freedom, direct-drive robot manipulator.

Adaptive Control Scheme for Visual Servo Manipulator Based On the Dead Zone Mathematical Model

In this paper, a PD control algorithm based on fuzzy logic dead compensation has been proposed. The fuzzy logic dead zone compensator was used to compensate the dead zone which existed in the mechanical system, PD control scheme was used to control trajectory of the joints of robot, so that the stability and robustness can be improved. In order to verify the validity of the control algorithm, we realized the proposed adaptive control strategy in MATLAB. The simulation results has revealed that:comparing with the traditional PD control scheme, the proposed PD control algorithm based on fuzzy logic dead compensation can effectively compensate the dead zone which existed in the mechanical system, also the position tracking performance and precision of the manipulator has been enhanced.

A naive method of applying fuzzy logic to CMAC in electric load simulator

The inherent non-linear factors and the interference of external surplus torque of the electric load simulator make it difficult for the conventional control methods to achieve satisfactory control effect. The cerebellar model articulation controller (CMAC) is widely used because of its simple structure and quick learning. However, conventional CMAC utilizes binary 0 and 1 logic, which will lead to the divergence during the torque tracking. Inspired by the cognitive characteristics of the human brain, the fuzzy logic is implemented to CMAC. In this paper, we design a naive method of applying fuzzy logic to CMAC (NFCMAC), which can take both advantages of the local neural network and the global neural network, and present a new interpretation of the entire network. With parallel control of a PD controller, the NFCMAC–PD control strategy has been successfully applied to the electric load simulator. Dynamic simulation and experimental results have indicated that the NFCMAC–PD control strategy can ensure the control precision, restrain interference and be free of divergence, while satisfy the control requirement of the passive loading system.

Unbounded regulators with variable gains for a direct-drive robot manipulator

This paper addresses the position-control problem with variable gains for robot manipulators. We present a new regulator based on a hyperbolic-sine structure with tuning rules for control gains. It is demonstrated that the equilibrium point of the closed-loop system is globally, asymptotically stable according to Lyapunov theory. By using a similar methodology, this concept can be extended to other unbounded controllers such as PD and PID. In order to show the usefulness of the proposed scheme and with the purpose of validating its asymptotical stability property, an experimental comparison involving constant gains controllers, for example: simple PD, PID and hyperbolic-tangent schemes vs variable-gains hyperbolic-sine and PD control schemes, was performed by using a three degree-of-freedom, direct-drive robot manipulator.

Cable driven robot as a blackboard writer for remote classrooms: modelling, control and trajectory planning

A remote classroom is one of the successful technologies to share knowledge beyond boundaries and to a large population. But the remote classroom demands for high-end visual systems to display the teachers' writings, which are costly and cannot be afforded by all. This paper presents an alternate idea of using a cable driven robot as a blackboard writer, which is able to replicate the teachers' writing on a blackboard. A planar fully constraint cable driven robot with a writer as an end-effectors is employed as a blackboard writer. It is basically an X-Y plotter that navigates on the planar plane according to the desired trajectory. A novel method for trajectory planning called 'appending trajectory points' was also introduced such that the CDR can faithfully follow the trajectory. The trajectory planner appends trajectory points to decrease the rate change and achieve bumpless transfer in the trajectory. An adaptive PD control scheme was employed for closed loop control to track the trajectory. Finally, the performance of the proposed controller was compared with the conventional PD controller and results are discussed in detail.

Disturbance-Observer-Based PD Control of Flexible Joint Robots for Asymptotic Convergence

This paper proposes a robust PD control scheme for flexible-joint robots based on a disturbance observer (DOB). In this paper, the DOB is applied only to the motor-side dynamics of the robot, and the uncertainties on the motor-side are successfully eliminated. It is shown that the proposed DOB-based approach guarantees global asymptotic stability. To this end, two special treatments are required. First, unlike the typical configuration of the DOB, nominal states of the motor-side are fed back to the PD controller. Second, a control input that makes the nominal states stable is additionally introduced. The proposed approach was verified using multi-degree-of-freedom experiments.