Model Control Method Research Articles

Torque ripple compensation control for hybrid UGVs in mode transition based on current harmonic control of a PMSM

Load jumping and mode transitions both cause the unstable dynamic states for compound power-split hybrid Unmanned Ground Vehicles (UGVs), and these phenomena lead to vibrations of the transmission system and longitudinal buffeting of the vehicle. This study presents a feed-forward compensation control strategy for load jumping and mode transitions to reduce the corresponding torsional vibration in hybrid UGVs. The proposed method injects an appropriate harmonic current into a permanent magnet synchronous motor (PMSM) to generate a harmonic torque that is opposite to the load torque, which improves the dynamic response quality of the vehicle load. First, the multimode structure of a hybrid UGV and mode switching vibration and shock are investigated, as well as a feed-forward compensate control architecture is proposed. Second, two models are established the PMSM dynamic model based on the electromagnetic coupling principle and a 2-degree-of-freedom torsional vibration model of transmission system by simplifying the vehicle system. Third, the harmonic current injection method is proposed, and the harmonic current equation is derived. Based on the field-oriented control algorithm, a double closed-loop controller is designed for the torque and speed of the PMSM, and the internal model control method is applied to design the current controller. The simulation results show that the proposed strategy effectively suppresses jerk and that the harmonics current transfers the energy from the mechanical vibrations of the system into electric power fluctuations.

Lane-Change Model and Tracking Control for Autonomous Vehicles on Curved Highway Sections in Rainy Weather

In this study, we propose an adaptive path planning model and tracking control method for collision avoidance and lane-changing manoeuvres on highways in rainy weather. Considering the human-vehicle-road interaction, we developed an adaptive lane change system that consists of an intelligent trajectory planning and tracking controller. Gaussian distribution was introduced to evaluate the impact of rain on the pavement characteristics and deduce adaptive lane-change trajectories. Subsequently, a score-based decision mechanism and multilevel autonomous driving mode that considers safety, comfort, and efficiency were proposed. A tracking controller was designed using a linearised model predictive control method. Finally, using simulated scenarios, the feasibility and effectiveness of the proposed method were demonstrated. The results obtained herein are a valuable resource that can be used to develop an intelligent lane change system for autonomous vehicles and can help improve highway traffic safety and efficiency in adverse weather conditions.

Learning adversarial policy in multiple scenes environment via multi-agent reinforcement learning

ABSTRACT Learning adversarial policy aims to learn behavioural strategies for agents with different goals, is one of the most significant tasks in multi-agent systems. Multi-agent reinforcement learning (MARL), as a state-of-the-art learning-based model, employs centralised or decentralised control methods to learn behavioural strategies by interacting with environments. It suffers from instability and slowness in the training process. Considering that parallel simulation or computation is an effective way to improve training performance, we propose a novel MARL method called Multiple scenes multi-agent proximal Policy Optimisation (MPO) in this paper. In MPO, we first simulate multiple parallel scenes in the training environment. Multiple policies control different agents in the same scene, and each policy also controls several identical agents from multiple scenes. Then, we expand proximal policy optimisation (PPO) with an improved actor-critic network, ensuring the stability of training in multi-agent tasks. The actor network only uses local information for decision making, and the critic network uses global information for training. Finally, effective training trajectories are computed with two criteria from multiple parallel scenes rather than single to accelerate the learning process. We evaluate our approach in two simulated 3D environments, one of which is Unity's official open-source soccer game, and the other is unmanned surface vehicles (USVs) built by Unity. Experiments demonstrate that MPO converges more stable and faster than benchmark methods in model training, and demonstrates excellent adversarial policy compared with benchmark models.

Establishment of energy consumption model and multi-objective optimal control method of 6-DOF robotic crusher

In order to optimize the real-time crushing effect of 6-DOF robotic crusher, a model of energy consumption and a multi-objective optimization control method for 6-DOF robotic crusher are proposed. In optimization function, the optimization objective are total energy consumption, mass fraction of crushed products below 12 mm, energy consumption ratio, and throughput, and optimization variables are position of suspension point, rotational speed and precession angle of the moving cone. Among them, the function of total energy consumption and effective energy consumption is established and the function of total energy consumption is verified in this paper. The function of mass fraction of crushed products below 12 mm is based on previous research. Taking the full load working condition and chamber size of PYGB1821 crusher as an example. The solution of optimization is obtained. Compared with the traditional cone crusher under the same feed size distribution and chamber size, each objective can be effectively optimized, which can effectively reduce energy consumption and increase the crushing efficiency. This method is universal and can be used for the design and control of other crushing equipment.

A Power Optimization Control Method Based on IMC for 3D Printer

Aiming at the effect of selective laser sintering technology used in 3D printing, the recursive least squares method was applied to fitting a control system model for quantification the relationship between laser power and corresponding temperature in this paper. The internal model control method is considered based on the establishing model. The controller is put into the actual 3D printing power control system for controlling the laser power. In the experiment, both internal model controller and the PID controller for the 3D printer are researched and deployed for comparing the their effects in the paper. The experimental result illustrates that the IMC based on the recursive least squares method is of effectiveness.

Standing balance maintenance by virtual suspension model control for legged robot

Legged robots demand to keep the balance under required durations when performing standing and locomotion. It may be a challenge for legged robots to maintain balance during standing without actuation from ankle joints and involvement of support polygon plane to estimate the center of mass (CoM). In order to maintain the standing balance of legged robots under such a scenario, we propose a virtual suspension model control (VSMC) method which is concise and can get rid of updating model iterations on sophisticated dynamics. Furthermore, we optimize the range and propose the criteria for the virtual height of the CoM for quickly adjusting parameters and adapting to task characteristics. Simulation experiments on balance keeping are performed for single-leg robot vertical standing, quadruped robot diagonal standing and biped robot parallel standing cases, and the proposed method can achieve promising results within the approximative real setting condition that demonstrate the feasibility and strong anti-interference ability of the VSMC approach.

A multiple-model based internal model control method for power control of small pressurized water reactors

Small pressurized water reactors (PWRs) usually have variable operating conditions and complex operating environments. It is significant to design a robust control system to ensure stable and satisfactory reactor power maneuvers under large uncertainties. This paper purposes a multiple-model based internal model control (IMC) method for power control of small PWRs. Six local transfer function models are first developed from a nonlinear reactor core model over the entire operating range. Then, six local power controllers are designed for a small PWR based on these local models using the IMC scheme. The IMC filter time constant is determined by the genetic algorithm based multi-objective optimization to keep good balance between the control performance and cost. The local controllers are connected by a probability-weighted multiple model approach to generate a global IMC system for the reactor. Dynamic simulation results of the small PWR under the IMC scheme as well as performance assessments of the IMC scheme against the PID control scheme during typical transient operations have shown good reference tracking performances and strong disturbance rejection capabilities of the multiple-model based IMC system, demonstrating the feasibility and effectiveness of the proposed method for the power control of small PWRs.

Trotting Control of Load-Carrying Quadruped Walking Vehicle with Load Variations Based on the Centroidal Dynamics and Adaptive Sliding Mode Control

Aiming at the control problems for load variations of the load-carrying quadruped walking vehicle, the method combining centroidal dynamics and adaptive sliding mode control is proposed to ensure the weight adaptation and improve the tracking accuracy of forward speed and lateral speed. The motion control of the walking vehicle is divided into two parts: torso motion control and swinging legs motion control. The control methods of centroidal dynamics and task space PD are applied to the motion control of the torso, and the virtual model control method is applied to the motion control of swinging legs. Then, the adaptive sliding mode control algorithm is applied in the height direction of the vehicle to realize the adaptation to weight change and the weight identification, and the tracking accuracy of forward speed and lateral speed is improved by combining the centroidal dynamics. Adams and Simulink are used to simulate the trotting gait on the flat ground and slope when the weight of walking vehicle changes, and comparisons are made with the virtual model control method. The results show that the method combining centroidal dynamics and adaptive sliding mode control can realize the adaptability to load variations and reduce the forward speed and lateral speed tracking error, which proves the effectiveness of the proposed control method.

Control of trotting gait for load-carrying quadruped walking vehicle with eccentric torso

Aiming at the problems of common methods in trotting gait control of a load-carrying quadruped walking vehicle, a control method, combining virtual model and centroidal dynamics, is proposed. The control of the walking vehicle is divided into two parts, meaning the motion control of the vehicle body and the motion control of the swing leg. The virtual model control method is used to work out the accelerations of the vehicle body, while the centroidal dynamics approach is used to obtain the resultant forces acting on the vehicle. Next, quadratic programming is used to distribute the resultant forces to the foot-ends of the supporting legs. Last, combining the Jacobian matrices of supporting legs, the vehicle body’s motion control is achieved. The virtual forces, acting on the swing leg foot-end, are obtained using the virtual model control method. Combining the swing leg’s Jacobian matrix, joint torques of swing leg are worked out. Simulink and Adams are adopted to jointly simulate omnidirectional trotting of the vehicle, under the condition of fixed and shifting position of eccentric weight. The effects of the virtual model and centroidal dynamics control method are compared with that of the virtual model control method. The results show that the errors of roll angle and pitch angle are reduced by 50%, 89% and 50%, 80%, respectively, as derived by virtual model and centroidal dynamic control method, under the two conditions. The proposed control algorithm is proved effective.

Dynamic modeling and trajectory tracking control method of segmented linkage cable-driven hyper-redundant robot

The dynamics modeling and trajectory optimization of a segmented linkage cable-driven hyper-redundant robot (SL-CDHRR) become more challenging, since there are multiple couplings between the active cables, passive cables, joints and end-effector. To deal with these problems, this paper proposes a dynamic modeling and trajectory tracking control methods for such type of CDHRR, i.e., SL-CDHRR. First, the multi-coupling kinematics equation (i.e., cable-joint-end) of the hyper-redundant robot is derived. Then, according to the transmission characteristics of the hybrid active/passive segmented linkage, the dynamic equation of series–parallel coupling is derived. It consists of parallel-active dynamics and series-passive dynamics. Furthermore, using the tension of active cables and the pose of the end-effector as optimization indicators, a trajectory tracking framework was constructed by the combination of dynamic feedforward control and PD control. The multi-objective particle swarm optimization method is used to achieve the simultaneous optimization of the energy indicator and control accuracy indicator during the trajectory tracking process. Finally, a MATLAB/SimMechanics co-simulation system is built, and the proposed methods are verified by the built co-simulation system.

Experimental Verification of Robust PID Controller Under Feedforward Framework for a Nonminimum Phase DC–DC Boost Converter

This article addresses the disturbance rejection problem of a nonminimum phase dc-dc boost converter operating in the continuous conduction mode (CCM) using a novel robust proportional-integral-derivative (PID) controller design method. The proposed idea is to design the controller using the equivalent feedforward formulation of the modified direct synthesis (MDS) approach. The advantages of the proposed MDS design are: 1) systematic incorporation of disturbance dynamics and the converter dynamics explicitly in the controller design to reduce the complex tuning effort of the controller parameters; 2) allowing the converter to operate close to the performance limit set by the zero in the right half-plane (RHP); 3) the closed-loop performance specifications can be incorporated into the desired loop response using only single tuning parameter based on Bode's gain crossover frequency inequality; 4) attenuates the loop gain to improve the disturbance rejection; and 5) realization of controller requires only output voltage as a feedback signal. The strength of the proposed MDS method is compared with the internal model control (IMC) method in both simulations and experiments. Based on these responses, the proposed PID ensures robust performance to the model-plant mismatch and allows the output voltage to quickly recover back to the operating voltage in the presence of external disturbances with less inductor current.

The influence of rate limit on proportional–integral controller for first-order plus time-delay systems

The control performance can be worsened by actuator rate limit, which can result in amplitude attenuation and phase delay in process control. In some extreme situations, actuator rate limit may bring about the system non-convergence. This paper focuses on the control difficulties and solutions of first-order plus time-delay (FOPTD) systems caused by rate limit. The influence of rate limit on stability regions of proportional–integral (PI) controller is analysed. Results show that a small rate limit value can reduce stability regions of PI parameters greatly. The negative correlation between the integral gain and the onset frequency, and the positive correlation between the proportional gain and the onset frequency are conducted. Moreover, the control performance of different PI tuning rules such as Skogestad internal model control, integral gain maximization, delay robustness-constrained optimization and Tyreus–Luyben​ tuning rules is evidently affected by rate limit. Simulation and experiment results verify that the PI controller tuned by Skogestad internal model control (SIMC) method is less sensitive to the rate limit variation and is more suitable for processes (the normalized dead-time is from 0.03 to 1) which have severe actuator rate limit. Tyreus–Luyben tuning rule is another optional method. In addition, the reasons why SIMC is not sensitive to rate limit variation are analysed. These analytical results can offer a guideline for practical applications.

Quantifying cumulative effectiveness of green stormwater infrastructure in improving water quality

Stormwater runoff is one of the main sources of pollution in streams and receiving water bodies of major cities. Green Stormwater Infrastructure (GSI) is a set of distributed stormwater best management practices that absorb excess water, filter out sediment and pollutants, and help recharge groundwater.Despite the increasing popularity of GSI as means of stormwater management, our knowledge of their cumulative performance is limited. In this research, we apply an empirical approach to study the effectiveness of GSI in improving the water quality of four major receiving water bodies of Seattle, Washington, at the watershed scale. We use a Bayesian structural time series model and synthetic control method to build counterfactual scenarios of water quality in absence of GSI implementation and estimate the causal impact of GSI on water quality. We use monthly time series data of water quality parameters (water temperature, dissolved oxygen, surface PAR, chlorophyll a, Secchi depth, pH, light transmission, and fecal coliform) in Seattle's urban watersheds from 2004 to 2017. We also use a set of nine control variables to estimate the counterfactual water quality parameters. Our findings show that GSI improve some water quality parameters such as chlorophyll a, light transmission and Secchi depth, but increase water temperature and decrease dissolved oxygen in some water bodies.

A Digital Internal Model Current Controller for Salient Machines

The performance of anisotropic electrical machines is strongly dependent on the current loop characteristics. The problems for achieving robustness and fast response, without overshoot and oscillations, are mainly related to different values and behavior of the direct and quadrature inductances (L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> , L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</sub> ), as well as to high output frequencies. In this article, a novel current controller structure based on internal model control method is presented, taking into account the magnetic anisotropy (L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> ≠ L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</sub> ). The model of salient machines is derived directly in the discrete domain and used to obtain a model-based controller. The controller derivation does not rely on transport-delay approximations, which enables improved decoupling of axes dynamics and the closed-loop robustness for very high output frequencies. The presented controller enables enhanced response for higher current loop bandwidth and output frequencies than the state-of-the-art methods. The experimental verification is performed on a three-phase synchronous machine, using a standard industrial three-phase inverter.

An improved 2-degree-of-freedom internal model proportional–integral–derivative controller design for stable time-delay processes

In this article, an enhanced 2-degree-of-freedom internal model control strategy for typical industrial processes with time-delay is developed. For the proposed controller, it is composed of an inner loop feedback controller which is designed based on the internal model control theory and a weighted set-point tracking controller. Note that the adjustment of set-point tracking performance and disturbance rejection characteristics can be decoupled by employing the developed strategy, which indicates that more degrees of freedom are obtained for the proposed controller design; thus, better ensemble performance and stronger robustness are anticipated by regulating these two controllers separately, which may not be achieved in the conventional internal model control method. Case studies on two kinds of stable processes with time-delay verify the effectiveness of the proposed scheme finally.

Internal Model Control Tuned Proportional Integral Derivative for Quadrotor Unmanned Aerial Vehicle Dynamic Model

In recent times, there are has been growing substantive attention to the quadrotor Unmanned Aerial Vehicle (UAV) stability control. However, inherent nonlinearity is a major challenge with this control technique, this paper, therefore, developed a PID based Internal Model Control (IMC) method for the dynamic model of quadrotor UAV. The versatility and simplicity of the Proportional-Integral-Derivative (PID) controller enable it to enjoy wide usage and acceptability as stability control methods for the unmanned aerial vehicles. The aim of this paper is to use the PID controller with IMC to control a UAV. The proposed approach - IMC-PID control method -was simulated using MATLAB software and X-plane flight simulator. Thereafter, a comparative analysis of the IMC-PID control method with Chien-Hrones-Reswick, Cohen-coon, and Ziegler Nichols based PID Controllers was done using pitch and altitude as performance metrics. Keywords: Internal Model Control,MATLAB/Simulink , Proportional Integral Derivative, Quadrotor, Unmanned Aerial Vehicle (UAV),X-Plane, DOI: 10.7176/CTI/9-01 Publication date: April 30 th 2020

Modeling control methods to manage the sylvatic plague in black‐tailed prairie dog towns

AbstractBlack‐tailed prairie dogs (Cynomys ludovicianus) are a keystone species of shortgrass and midgrass prairies, and they are essential for successful reintroduction efforts of endangered black‐footed ferrets (Mustela nigripes). Sylvatic plague extirpates black‐tailed prairie dog colonies. We present a model to determine optimal control methods to sustain a black‐tailed prairie dog colony against the plague, including a recently developed vaccine. Our host submodel is a susceptible, exposed, infectious, vaccinated model, and our vector submodel is a susceptible, exposed, early‐stage and late‐stage infectious model with questing and on‐host vectors. Both submodels are hybrid ordinary differential and difference equation models to reflect the phenology of black‐tailed prairie dogs. Our model suggests vaccination efforts can substantially outperform previous control methods (e.g. reactive insecticidal dusting). Our model suggests that a vaccine that provides 18 months of immunity, administered annually, starting one year before an outbreak, can efficiently sustain a black‐tailed prairie dog colony against the plague.Recommendations for resource managers The current sylvatic plague vaccine, administered annually, is insufficient to protect a black‐tailed prairie dog colony against the sylvatic plague. Developing a vaccine with an immunity period of 18 months is critical for the persistence of a colony against the plague. While insecticidal dusting appears unable to assist in helping a black‐tailed prairie dog colony recover from a plague outbreak, insecticidal dusting is still a critical prevention tool as plague transmission from the prairie dog flea is capable of causing a plague outbreak by itself. Black‐tailed prairie dog colony recovery efforts appear sensitive to regularly administered culling. We recommend that colonies that are designated as part of the black‐footed ferret recovery program be protected from population losses from recreational hunting and poisoning.

Current Control Methods for an Asymmetric Six-Phase Permanent Magnet Synchronous Motor

Via the vector space decomposition (VSD) transformation, the currents in an asymmetric six-phase permanent magnet synchronous motor (ASP_PMSM) can be decoupled into three orthogonal subspaces. Control of α–β currents in α–β subspace is important for torque regulation, while control of x-y currents in x-y subspace can suppress the harmonics due to the dead time of converters and other nonlinear factors. The zero-sequence components in O1-O2 subspace are 0 due to isolated neutral points. In α–β subspace, a state observer is constructed by introducing the error variable between the real current and the internal model current based on the internal model control method, which can improve the current control performance compared to the traditional internal model control method. In x–y subspace, in order to suppress the current harmonics, an adaptive-linear-neuron (ADALINE)-based control algorithm is employed to generate the compensation voltage, which is self-tuned by minimizing the estimated current distortion through the least mean square (LMS) algorithm. The modulation technique to implement the four-dimensional current control based on the three-phase SVPWM is given. The experimental results validate the robustness and effectiveness of the proposed control method.

The Generalized Internal Model Control Method

The work deals with a generalization of the internal model control method whereby the original process model is suitably simplified to facilitate direct parameterization of feedback controllers. Here, the m/n moment approximant is adopted as the simplified model. The parameterized feedback controller contains a filter that can the tuned for closed loop system acceptable characteristics. The method facilitates cheap computation of controllers satisfying desired performance and stipulated constraints.

Model Identification and Internal Model Control for 3D Printer

A 3D printer system for selective laser sintering technology is used to establish a mathematical model of the relationship between laser power and temperature by using the recursive least squares method. Based on this model, the internal model control method is used to design the controller to realize the actual 3D printer. Temperature control, simulation analysis of internal model control and traditional PID control effects. The experimental results show that the feasibility, accuracy and internal model control of the recursive least squares identification model are fast, easy to implement, robust, and only one adjustable parameter, easy to adjust.