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The magnetic levitation ball system is characterized by strong nonlinearity, multiple disturbances, and intrinsic instability, which has long been a thorny problem in the field of control engineering. The magnetic levitation system can be continuously and stably levitated, even in a complex environment. In this thesis, the model of the magnetic levitation ball system is firstly constructed according to the kinetic theory and simplified according to the actual situation. After that, a linear active disturbance rejection control (LADRC) controller for the magnetic levitation ball system is designed. Considering that there are many parameters in the LADRC controller and it is difficult to obtain the optimal control effect by manual tuning, an adaptive variable gain LADRC algorithm is proposed to optimize the control strategy of LADRC parameters. An adaptive iterative algorithm is used to adaptively adjust the bandwidth of the linear extended state observer (LESO) in LADRC, and the convergence of the algorithm is demonstrated by using the Lyapunov function. To solve the problem that the proportional and differential gains of the LADRC controller can only be adjusted unidirectionally and simultaneously, this paper proposes an error variable gain algorithm. The aim is to realize the non-unidirectional and more detailed adjustment of the controller parameters, and it is rigorously analyzed and demonstrated through simulation and experiment. The results show that the proposed algorithm is better than proportional–integral–derivative (PID), sliding mode control (SMC), and LADRC in terms of dynamic performance, steady-state performance, and anti-interference.

This paper presents the realization of high gain low Noise Figure (NF) Low Noise Amplifier (LNA) employing the variable gain amplifier. The high gain is achieved by cascading three stages while the low NF is achieved by employing the resistive feedback in the input stage. The linearity is achieved by employing the source degeneration technique. The variable gain amplifier gets turned on/off by the input signal causing the change in the transconductance of the LNA and hence the gain of LNA varies according to the input signal strength. The results show that maximum gain for the realized LNA is 21.34 dB at 1.72 GHz for M7 ON position while during M7 OFF position, the maximum gain achieved is 26.05 dB at 1.72 GHz frequency. The S11 value is less than –9 dB for the frequency range of 1.65 GHz to 3.9 GHz, i. e., having the bandwidth of 2.25 GHz and it is matched for the 50 Ω termination at input and output port. The minimum value of the NF during low conductance is 2.88 dB while during the high conductance it is 2.82 dB.

This paper investigates the distributed adaptive platoon tracking problem of third-order heterogeneous vehicles subject to model uncertainties. The design process is divided into two steps. Firstly, an adaptive tracking controller is designed for the dynamic leading vehicle. And then, the distributed adaptive controllers are established for followers. Moreover, the predictor technique is used to improve the estimate performance of the adaptive law, and the total disturbance is approximated and compensated by the variable gain nonlinear extended state observers (NESOs) driven by the estimation error. By introducing the variable gain hyperbolic tangent tracking differentiator (HTTD), the “complexity explosion” problem is avoided. The feasibility and effectiveness of the proposed protocol are verified by simulation tests.

In recent times, a variety of reinforcement learning (RL) algorithms have been proposed for optimal tracking problem of continuous time nonlinear systems with input constraints. Most of these algorithms are based on the notion of uniform ultimate boundedness (UUB) stability, in which normally higher learning rates are avoided in order to restrict oscillations in state error to smaller values. However, this comes at the cost of higher convergence time of critic neural network weights. This paper addresses that problem by proposing a novel tuning law containing a variable gain gradient descent for critic neural network that can adjust the learning rate based on Hamilton–Jacobi–Bellman (HJB) approximation error. By allowing high learning rate the proposed variable gain gradient descent tuning law could improve the convergence time of critic neural network weights. Simultaneously, it also results in tighter residual set, on which trajectories of augmented system converge to, leading to smaller oscillations in state error. A tighter bound for UUB stability of the proposed update mechanism is proved. Numerical studies are then furnished to validate the variable gain gradient descent-based update law presented in this paper on a continuous time nonlinear system.

This paper proposes a novel nonlinear speed control method for permanent magnet synchronous motors that enhances their robustness and tracking performance. This technique integrates a sliding-mode disturbance observer and variable-gain fractional-order super-twisting sliding-mode control within a vector-control framework. The proposed control scheme employs a sliding-mode control method to mitigate chattering and improve dynamics by implementing fractional-order theory with a variable-gain super-twisting sliding manifold design while regulating the speed of the considered motor system. The aforementioned observer is suggested to enhance the control accuracy by estimating and compensating for the lumped disturbances. The proposed methodology demonstrates its superiority over other control schemes such as traditional sliding-mode control, super-twisting sliding-mode control, and the proposed technique. MATLAB/Simulink simulations and real-time implementation validate its performance, showing its potential as a reliable and efficient control approach for the system under study in practical applications.

Disturbance observer (DOB) based controller performs well in estimating and compensating for perturbation when the external or internal unknown disturbance is slowly time varying. However, to some extent, robot manipulators usually work in complex environment with high-frequency disturbance. Thereby, to enhance tracking performance in a teleoperation system, only traditional DOB technique is insufficient. In this paper, for the purpose of constructing a feasible teleoperation scheme, we develop a novel controller that contains a variable gain scheme to deal with fast-time varying perturbation, whose gain is adjusted linearly according to human surface electromyographic signals collected from Myo wearable armband. In addition, for tracking the motion of operator’s arm, we derive five-joint-angle data of a moving human arm through two groups of quaternions generated from the armbands. Besides, the radial basis function neural networks and the disturbance observer-based control (DOBC) approaches are fused together into the proposed controller to compensate the unknown dynamics uncertainties of the slave robot as well as environmental perturbation. Experiments and simulations are conducted to demonstrated the effectiveness of the proposed strategy.

We demonstrate a low-power ( P dc ) 25.5–30.7 GHz CMOS variable-gain amplifier (VGA). The VGA constitutes a common-source (CS) input stage (M 1 ), followed by current-reused CS gain (M 2 ) and output stages (M 3 ). Transistors M 1 -M 3 adopt the topology of B-to-D with R B , i.e., body terminal is connected to drain via a large resistance R B , for body self-forward-bias and floating (BSFBF). This leads to gain boosting and NF reduction of the VGA at the same P dc due to larger transconductance g m (because of larger bias current) and smaller bias voltage, and effective suppression of the substrate leakage and noise. Simultaneous input and noise matching are achieved by suitable selection of the size and bias of M 1 , and the inductance of L g1 and L 1 . Analog switch transistor M 4 is in parallel with M 3 to tune its overdrive (V OV ) and drain-source voltage (V DS ) for fine tuning of S 21 . Digital switch transistor M 5 (in conjunction with the series coupling capacitance C C and resonant inductance L 10 ) is in parallel with M 2 to control its AC V DS for coarse tuning of S 21 . In the case of M 5 being turned-on, the series of C C -M 5 -L 10 is close to a short-circuit (~ 4.6 Ω) at the output node of M 2 over the 3-dB gain bandwidth (f 3dB ) of 18.4–30.7 GHz. This leads to S 21 tuning range boosting. Moreover, M 4 -M 5 adopt DTMOS with R B , i.e., body of M 4 -M 5 is connected to gate via R B , for BSFBF to lower the on-state channel resistance ( R ch ) and increase the off-state R ch . Further S 21 tuning range boosting is attained. The VGA consumes 9 mW, and achieves S 21 of 15.4 ± 1.5 dB for 18.4–30.7 GHz, tuning range of 29.8 dB (15.5 ~ − 14.3 dB) at 28 GHz, average NF (NF avg ) of 2.79 dB for 18–31 GHz, and figure-of-merit (FOM) of 2.24 GHz. The NF avg and FOM are one of the best results ever reported for wideband VGAs/LNAs with P dc lower than 10 mW. The eminent results of the VGA indicate it is suitable for 28 GHz 5G systems.

The paper presents an automatic frequency calibration (AFC) technique for a charge pump-based phase-locked loop (CPPLL) with 5–6 μsec correction time. The architecture detects frequency offset in real time while keeping the loop active and performs a variable gain calibration that increases the correction gain at large frequency offsets to accelerate lock acquisition and gradually reduce the gain near locking frequency to suppress residual oscillation and overshoot. The implemented synthesizer rapidly re-acquires the lock within several adjacent coarse-tuning codes after frequency drift and maintains continuous operation without interruption. It demonstrates that the designed AFC achieves seamless frequency recovery in dynamically varying environments. Fabricated in a 65 nm CMOS process, the prototype fractional-N synthesizer occupies an active area of 0.603 mm2 and operates over a 5.3–6.2 GHz tuning range. At 5.8 GHz, the design achieves a phase noise of −107 dBc/Hz at 1 MHz offset and consumes 21.5 mW from a 1.2 V supply.

To improve the adaptability of sensorless control in the full-speed range of a dual three-phase permanent magnet synchronous motor (DTP-PMSM), an improved sensorless control strategy based on a variable-gain super twisting algorithm sliding mode observer (VGSTA-SMO) along with harmonic component compensation has been introduced in this paper. First, the super twisting algorithm sliding mode observer (STA-SMO) is introduced to reduce the inherent chattering phenomenon of traditional SMOs. Then, the variable gain of this STA-SMO is designed to improve the observation adaptability at different rotor speeds. Meanwhile, considering that the harmonic components, especially at low rotor speeds, in the stator current can affect the observation accuracy of this VGSTA-SMO, a least mean squares adaptive notch filter (LMS-ANF) is employed to implement online harmonic compensation. Finally, comparative experiments with different methods in the full-speed range are conducted and compared to verify the effectiveness of the proposed novel sensorless control strategy whose observation deviation is about 2% even when the rotor speed is as low as 100 rpm.

The purpose of this paper is to study the sensor-less rotor position estimation method for permanent magnet synchronous motors, and to achieve accurate estimation of rotor position in different conditions. Firstly, the traditional super-twisting observer algorithm is analyzed, and a new discrete variable gain sliding mode observer is designed to solve the buffeting problem in discrete systems, taking the reaction force as the disturbance signal. By estimating the back potential of the observer, the buffeting problem in the sliding mode algorithm can be effectively improved as shown by the simulation results. Then, to solve the problem of phase delay in rotor position estimation, an adaptive orthogonal phase-locked loop method is used to compensate the estimation error caused by the change in motor speed and increase the estimation accuracy of rotor position. The stability of the method can be proven by Lyapunov’s second method. Simulation experiments verify the accuracy of the proposed PMSM rotor position estimation method.