Dynamics and adaptive control of a dual-arm space robot with closed-loop constraints and uncertain inertial parameters

A dynamics-based adaptive control approach is proposed for a planar dual-arm space robot in the presence of closed-loop constraints and uncertain inertial parameters of the payload. The controller is capable of controlling the po- sition and attitude of both the satellite base and the payload grasped by the manipulator end effectors. The equations of motion in reduced-order form for the constrained system are derived by incorporating the constraint equations in terms of accelerations into Kane＇s equations of the unconstrained system. Model analysis shows that the resulting equations perfectly meet the requirement of adaptive controller design. Consequently, by using an indirect approach, an adaptive control scheme is proposed to accomplish position/attitude trajectory tracking control with the uncertain parameters be- ing estimated on-line. The actuator redundancy due to the closed-loop constraints is utilized to minimize a weighted norm of the joint torques. Global asymptotic stability is proven by using Lyapunov＇s method, and simulation results are also presented to demonstrate the effectiveness of the proposed approach.

Application of Single Neuron Adaptive PID Regulators with Auto-tuning Gain in Industrial Parameter(Pressure)Closed-loop Process Control Systems

A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.

A Space Vector Modulation Based Three-level PWM Rectifier under Simple Sliding Mode Control Strategy

In this paper, a voltage oriented control strategy for three-level PWM rectifier based on Sliding Mode Control (SMC) is introduced in order to obtain fast and accurate response of dc-bus voltage. To verify the validity of the analysis and the feasibility of the proposed control method a set of simulation tests have been conducted using Matlab/Simulink. The simulation results show that compared to the conventional PI controller, the SMC can reduce drastically the three-level rectifier’s voltage fluctuation and improve the dynamic response of dc-bus significantly.

A Modified Neutral-point Voltage Control Strategy for Three-level Inverters Based on Decomposition of Space Vector Diagram

Capacitor voltage imbalance is a significant problem for three-level inverters.Due to the mid-point modulation of these inverter topologies,the neutral point potential moves up or down depending on the neutral point current direction creating imbalanced voltages among the two capacitors.This imbalanced capacitor voltage causes imbalanced voltage stress among the semiconductor devices and causes increase output voltage and current harmonics.This paper introduces a modified voltage balancing strategy using two-level space vector modulation.By decomposing the three-level space vector diagram into two-level space vector diagram and redistributing the dwell times of the two-level zero space vectors,the modified voltage balancing method ensures minimal NP voltage ripple.Compared to the commonly used NP voltage control method(using 3L SVM[9]),the proposed modified NP voltage control method offers a slightly higher neutral-point voltage ripple and output voltage harmonics but,it has much lower switching loss,code size and execution time.

Interference Management for DS-CDMA Systems through Closed-Loop Power Control, Base Station Assignment, and Beamforming

In this paper, we propose a smart step closed-loop power control (SSPC) algorithm and a base station assignment method based on minimizing the transmitter power (BSA-MTP) technique in a direct sequence-code division multiple access (DS-CDMA) receiver with frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with constrained least mean squared (CLMS) algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference (IPI) is reduced in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can use for more reduction of the IPI and MAI in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can significantly reduce the network bit error rate (BER) compared to the other methods. Also, we observe that significant savings in total transmit power (TTP) are possible with our methods.

Model Reference Adaptive Control for Switched Systems with Closed-loop Reference Model Under Arbitrary Switching

This paper explores the model reference adaptive control problem for a class of switched linear systems under arbitrary switching with no need for the measurability of the system state.Based on the state of reference model and the measurable output error, adaptive laws and controllers are designed for switched systems.Each subsystem may have its individual reference model and controller, which increases the design flexibility.The introduction of the closed-loop reference model is to get a better transient performance of the whole switched systems.A numerical example is provided to verify the effectiveness of the main results.

Joint Closed-Loop Power Control and Adaptive Beamforming for Wireless Networks with Antenna Arrays in a 2D Urban Environment

The interference reduction capability of antenna arrays and the power control algorithms have been considered separately as means to decrease the interference in wireless communication networks. In this paper, we propose smart step closed-loop power control (SSPC) algorithm in wireless networks in a 2D urban environment with constrained least mean squared (CLMS) algorithm. This algorithm is capable of efficiently adapting according to the environment and able to permanently maintain the chosen frequency response in the look direction while minimizing the output power of the array. Also, we present switched-beam (SB) technique for enhancing signal to interference plus noise ratio (SINR) in wireless networks. Also, we study an analytical approach for the evaluation of the impact of power control error (PCE) on wireless networks in a 2D urban environment. The simulation results indicate that the convergence speed of the SSPC algorithm is faster than other algorithms. Also, we observe that significant saving in total transmit power (TTP) are possible with our proposed algorithm. Finally, we discuss three parameters of the PCE, number of antenna elements, and path-loss exponent and their effects on capacity of the system via some computer simulations.

A Deep Reinforcement Learning-Based Power Control Scheme for the 5G Wireless Systems

In the fifth generation(5G)wireless system,a closed-loop power control(CLPC)scheme based on deep Q learning network(DQN)is introduced to intelligently adjust the transmit power of the base station(BS),which can improve the user equipment(UE)received signal to interference plus noise ratio(SINR)to a target threshold range.However,the selected power control(PC)action in DQN is not accurately matched the fluctuations of the wireless environment.Since the experience replay characteristic of the conventional DQN scheme leads to a possibility of insufficient training in the target deep neural network(DNN).As a result,the Q-value of the sub-optimal PC action exceed the optimal one.To solve this problem,we propose the improved DQN scheme.In the proposed scheme,we add an additional DNN to the conventional DQN,and set a shorter training interval to speed up the training of the DNN in order to fully train it.Finally,the proposed scheme can ensure that the Q value of the optimal action remains maximum.After multiple episodes of training,the proposed scheme can generate more accurate PC actions to match the fluctuations of the wireless environment.As a result,the UE received SINR can achieve the target threshold range faster and keep more stable.The simulation results prove that the proposed scheme outperforms the conventional schemes.

Data-Driven Model Identification and Control of the Inertial Systems

In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the system in the open loop. To tackle these difficulties, an approach of data-driven model identification and control algorithm design based on the maximum stability degree criterion is proposed in this paper. The data-driven model identification procedure supposes the finding of the mathematical model of the system based on the undamped transient response of the closed-loop system. The system is approximated with the inertial model, where the coefficients are calculated based on the values of the critical transfer coefficient, oscillation amplitude and period of the underdamped response of the closed-loop system. The data driven control design supposes that the tuning parameters of the controller are calculated based on the parameters obtained from the previous step of system identification and there are presented the expressions for the calculation of the tuning parameters. The obtained results of data-driven model identification and algorithm for synthesis the controller were verified by computer simulation.

Robot-Oriented 6G Satellite-UAV Networks: Requirements, Paradigm Shifts, and Case Studies

Networked robots can perceive their surroundings, interact with each other or humans,and make decisions to accomplish specified tasks in remote/hazardous/complex environments. Satelliteunmanned aerial vehicle(UAV) networks can support such robots by providing on-demand communication services. However, under traditional open-loop communication paradigm, the network resources are usually divided into user-wise mostly-independent links,via ignoring the task-level dependency of robot collaboration. Thus, it is imperative to develop a new communication paradigm, taking into account the highlevel content and values behind, to facilitate multirobot operation. Inspired by Wiener’s Cybernetics theory, this article explores a closed-loop communication paradigm for the robot-oriented satellite-UAV network. This paradigm turns to handle group-wise structured links, so as to allocate resources in a taskoriented manner. It could also exploit the mobility of robots to liberate the network from full coverage,enabling new orchestration between network serving and positive mobility control of robots. Moreover,the integration of sensing, communications, computing and control would enlarge the benefit of this new paradigm. We present a case study for joint mobile edge computing(MEC) offloading and mobility control of robots, and finally outline potential challenges and open issues.

Bioinspired Closed-loop CPG-based Control of a Robotic Manta for Autonomous Swimming

Fish in nature exhibit a variety of swimming modes such as forward swimming,backward swimming,turning,pitching,etc.,enabling them to swim in complex scenes such as coral reefs.It is still difficult for a robotic fish to swim autonomously in a confined area as a real fish.Here,we develop an untethered robotic manta as an experimental platform,which consists of two flexible pectoral fins and a tail fin,with three infrared sensors installed on the front,left,and right sides of the head to sense the surrounding obstacles.To generate multiple swimming modes of the robotic manta and online switching of different modes,we design a closed-loop Central Pattern Generator(CPG)controller based on distance information and use a combination of phase difference and amplitude of the CPG model to achieve stable and rapid adjustment of yaw angle.To verify the autonomous swimming ability of the robotic manta in complex scenes,we design an experimental scenario with a concave obstacle.The experimental results show that the robotic manta can achieve forward swimming,backward swimming,in situ turning within the concave obstacle,and finally exit from the area safely while relying on the perception of external obstacles,which can provide insight into the autonomous exploration of complex scenes by the biomimetic robotic fish.Finally,the swimming ability of the robotic manta is verified by field tests.

Sensor fault-tolerant observer applied in satellite attitude control

The observing failure and feedback instability might happen when the partial sensors of a satellite attitude control sys- tem （SACS） go wrong. A fault diagnosis and isolation （FDI） method based on a fault observer is introduced to detect and isolate the fault sensor at first. Based on the FDI result, the object system state-space equation is transformed and divided into a correspon- sive triangular canonical form to decouple the normal subsystem from the fault subsystem. And then the KX fault-tolerant observers of the system in different modes are designed and embedded into online monitoring. The outputs of all KX fault-tolerant observers are selected by the control switch process. That can make sense that the SACS is part-observed and in stable when the partial sen- sors break down. Simulation results demonstrate the effectiveness and superiority of the proposed method.

Digital pulsed MIG welding machine based on adaptive fuzzy controller

Digital pulsed metal inert gas welding machine with double closed-loop control mode is designed and implemented. It realizes precision control for real time energy and demonstrates the flexibility of digital control. Test results of design prototype show that the designed control strategy can effectively adapt to the change of arc length and achieve ideal droplet transfer via one drop per pulse mode. Thus the welding process is stable and the weld bead is good.

Stability analysis of a noise control system in a duct by using delay differential equation

The paper deals with the criteria for the closed- loop stability of a noise control system in a duct. To study the stability of the system, the model of delay differential equation is derived from the propagation of acoustic wave governed by a partial differential equation of hyperbolic type. Then, a simple feedback controller is designed, and its closed- loop stability is analyzed on the basis of the derived model of delay differential equation. The obtained criteria reveal the influence of the controller gain and the positions of a sensor and an actuator on the closed-loop stability. Finally, numerical simulations are presented to support the theoretical results.

Control of epileptiform spikes based on nonlinear unscented Kalman filter

A new control strategy based on nonlinear unscented Kalman filter(UKF) is proposed for a neural mass model that serves as a model for simulating real epileptiform stereo-electroencephalographic (SEEG) signals. The UKF is used as an observer to estimate the state from the noisy measurement because it has been proved to be effective for state estimation of nonlinear systems. A UKF controller is constructed via the estimated state and is illustrated to be effective for epileptiform spikes suppression of aforementioned model by numerical simulations.

Management strategy of prevention and control of nosocomial infection of COVID-19 in blood purification center

There are many patients in the blood purification center who need maintenance hemodialysis to maintain life. Those patients generally havelow resistance and are easily exposed to coronavirus because they go back and forth the hospital and residence three times a week andclosely contact with family, caregivers, community personnel, people in various means of transportation, medical staff, and other patientsvisiting hospital. Therefore, the blood purification center has become a high‑risk environment for the spread of COVID-19 infection. In viewof this, our center quickly responded to the formulation and implementation of infection prevention and control measures suitable for thecharacteristics of the blood purification center and continuous renal replacement therapy (CRRT) emergency plan for fever and suspectedpatients. According to these measures, we have a positive effect on preventing and controlling nosocomial infection in the blood purificationcenter.

Simulation of Automotive Engine Phase Signal Based on Closed-Loop Strategy

In this paper, an automotive engine phase signal simulation algorithm is proposed based on a closed-loop feedback strategy, and its corresponding model is built. The signal incentives are carried out in the front-end, and the synchronization capture and comparison are conducted in the back-end. The phase simulation of signal output is achieved using closed-loop strategy, which can effectively eliminate the inconsistency between crankshaft and camshaft phases, and thus the accuracy and flexibility of phase signal generation are guaranteed. Experimental results show that the proposed algorithm is real time, and the deviation of simulated signals from actual phase signals is small.

CONTINUOUS-TIME GENERALIZED PREDICTIVECONTROL WITH POLE-PLACEMENT

ＣＯＮＴＩＮＵＯＵＳ－ＴＩＭＥＧＥＮＥＲＡＬＩＺＥＤＰＲＥＤＩＣＴＩＶＥＣＯＮＴＲＯＬＷＩＴＨＰＯＬＥ－ＰＬＡＣＥＭＥＮＴＬｕＪｉａｎｈｏｎｇ（吕剑虹）ＸｕＺｈｉｇａｏ（徐治皋）ＣｈｅｎＬａｉｊｉｕ（陈来九）（ＤｅｐａｒｔｍｅｎｔｏｆＰｏｗｅｒＥｎｇ...

Parkinsonian oscillations and their suppression by closed-loop deep brain stimulation based on fuzzy concept

This paper provides an adaptive closed-loop strategy for suppressing the pathological oscillations of the basal ganglia based on a variable universe fuzzy algorithm.The pathological basal ganglia oscillations in the theta(4-9 Hz)and beta(12-35 Hz)frequency bands have been demonstrated to be associated with the tremor and rigidity/bradykinesia symptoms in Parkinson’s disease(PD).Although the clinical application of open-loop deep brain stimulation(DBS)is effective,the stimulation waveform with the fixed parameters cannot be self-adjusted as the disease progresses,and thus the stimulation effects go poor.To deal with this difficult problem,a variable universe fuzzy closed-loop strategy is proposed to modulate different PD states.We establish a cortico-basal ganglia-thalamocortical network model to simulate pathological oscillations and test the control effect.The results suggest that the proposed closed-loop control strategy can accommodate the variation of brain states and symptoms,which may become an alternative method to administrate the symptoms in PD.

PD Power-Level Control Design for MHTGRs

Due to its inherent safety feature, the modular high temperature gas-cooled reactor (MHTGR) has been seen as one of the best candidates in building next generation nuclear plants (NGNPs). Since the MHTGR dynamics has high nonlinearity, it is necessary to develop nonlinear power-level controller which is not only beneficial to the safe, stable, efficient and autonomous operation of the MHTGR but also easy to be implemented practically. In this paper, based on the concept of shiftedectropy and the physically-based control design approach, it is proved theoretically that the simple proportional-differential (PD) output-feedback power-level control can provide globally asymptotic closed-loop stability. Numerical simulation results verify the theoretical results and show the influence of the controller parameters to the dynamic response.