In this article, the problem of optimal time-varying attitude tracking control for rigid spacecraft with system constraints and unknown additive disturbances is considered. Through the design of a ...new nonlinear tube-based robust model predictive control (TRMPC) algorithm, a dual-loop cascaded tracking control framework is established. The proposed TRMPC algorithm explicitly considers the effect of disturbances and applies tightened system constraints to predict the motion of the nominal system. The obtained optimal control action is then combined with a nonlinear feedback law such that the actual system trajectories can always be steered within a tube region centered around the nominal solution. To facilitate the recursive feasibility of the optimization process and guarantee the input-to-state stability of the tracking control process, the terminal controller and the corresponding terminal invariant set are also constructed. The effectiveness of using the proposed dual-loop TRMPC control scheme to track reference attitude trajectories is validated by experimental studies. A number of comparative studies were carried out, and the obtained results reveal that the proposed design is able to achieve more promising constraint handling and attitude tracking performance than that of the other newly developed methods investigated in this research.
In this study, trajectory tracking of robotic manipulators under varying loads with uncertainties and external disturbances is obtained by proposing model‐independent adaptive fractional high‐order ...terminal sliding mode control (AFO‐HoTSMC). The proposed AFO‐HoTSMC method is composed of an adaptive high‐order terminal sliding mode control integrated with fractional‐order (FO) control. An adaptive tuning control is utilised to evaluate the uncertain unknown dynamics of the system without relying on the prior knowledge of the upper bounds. FO control and HoTSMC are used to achieve the fast finite‐time convergence, chatter‐free control inputs, better tracking performance and robustness. The finite‐time stability of the overall system is investigated and derived from the Lyapunov stability criterion. Finally, to validate the effectiveness and robustness of the developed control method, comparative simulations with H∞‐Adaptive control, intelligent PD (iPD), intelligent PID (iPID) and adaptive third‐order SMC (ATOSMC) are realized to demonstrate the performance of AFO‐HoTSMC.
Power electronics technology is still an emerging technology, and it has found its way into many applications, from renewable energy generation (i.e., wind power and solar power) to electrical ...vehicles (EVs), biomedical devices, and small appliances, such as laptop chargers. In the near future, electrical energy will be provided and handled by power electronics and consumed through power electronics; this not only will intensify the role of power electronics technology in power conversion processes, but also implies that power systems are undergoing a paradigm shift, from centralized distribution to distributed generation. Today, more than 1000 GW of renewable energy generation sources (photovoltaic (PV) and wind) have been installed, all of which are handled by power electronics technology. The main aim of this book is to highlight and address recent breakthroughs in the range of emerging applications in power electronics and in harmonic and electromagnetic interference (EMI) issues at device and system levels as discussed in ?robust and reliable power electronics technologies, including fault prognosis and diagnosis technique stability of grid-connected converters and ?smart control of power electronics in devices, microgrids, and at system levels.
Power electronics technology is still an emerging technology, and it has found its way into many applications, from renewable energy generation (i.e., wind power and solar power) to electrical ...vehicles (EVs), biomedical devices, and small appliances, such as laptop chargers. In the near future, electrical energy will be provided and handled by power electronics and consumed through power electronics; this not only will intensify the role of power electronics technology in power conversion processes, but also implies that power systems are undergoing a paradigm shift, from centralized distribution to distributed generation. Today, more than 1000 GW of renewable energy generation sources (photovoltaic (PV) and wind) have been installed, all of which are handled by power electronics technology. The main aim of this book is to highlight and address recent breakthroughs in the range of emerging applications in power electronics and in harmonic and electromagnetic interference (EMI) issues at device and system levels as discussed in ?robust and reliable power electronics technologies, including fault prognosis and diagnosis technique stability of grid-connected converters and ?smart control of power electronics in devices, microgrids, and at system levels.
The problem of adaptive fuzzy decentralized fault-tolerant optimal control is investigated for nonlinear large-scale systems with actuator faults in this paper. Fuzzy logic systems are utilized to ...approximate the unknown nonlinear functions and learn cost functions. Filtered signals are adopted to circumvent the problems of an algebraic loop on designing the decentralized controllers. Based on the backstepping technique and fault-tolerant control technique, a decentralized feedforward control strategy is designed. Based on the adaptive critic technique, a decentralized feedback optimal control strategy is designed. By combining the feedforward control strategy with the feedback optimal control strategy, a novel adaptive fuzzy decentralized fault-tolerant optimal control scheme is established. The stability of the closed-loop system is proved by using the Lyapunov stability theory. The effectiveness of the proposed decentralized control approach is confirmed via a simulation example.
In this paper, an adaptive trajectory tracking control algorithm for underactuated unmanned surface vessels (USVs) with guaranteed transient performance is proposed. To meet the realistic dynamical ...model of USVs, we consider that the mass and damping matrices are not diagonal and the input saturation problem. Neural networks (NNs) are employed to approximate the unknown external disturbances and uncertain hydrodynamics of USVs. Moreover, both full-state feedback control and output feedback control are presented, and the unmeasurable velocities of the output feedback controller are estimated via high-gain observer. Unlike the conventional control methods, we employ the error transformation function to guarantee the transient tracking performance. Both simulation and experimental results are carried out to validate the superior performance via comparing with traditional potential integral control approaches.
Shunt active power filters have been proved as useful elements to correct distorted currents caused by nonlinear loads in power distribution systems. This paper presents an all-digital approach based ...on a particular repetitive control technique for their control. Specifically, a digital repetitive plug-in controller for odd-harmonic discrete-time periodic references and disturbances is used for the current control loops of the active filter. This approach does not introduce a high gain at those frequencies for which it is not needed and, thus, improves robustness of the controlled system. The active power balance of the whole system is assured by an outer control loop, which is designed from an energy-balancing perspective. The design is performed for a three-phase four-wire shunt active filter with a full-bridge boost topology. Several experimental results are also presented to show the good behavior of the closed-loop system
This paper presents a comparative study of two predictive speed control schemes for induction machine (IM) in terms of their design and performance. The first control scheme is finite control ...set-model predictive control (FCS-MPC) with modulation control and the second control scheme is continuous control set-model predictive control (CCS-MPC) with space vector-pulse width modulation. The two schemes adopt the cascaded control approach, which consists of an inner MPC loop for torque control and outer MPC loop for speed control using two individual cost functions. The outer MPC produces the required torque to drive the IM at the reference speed while the reference torque is taken as the input of the inner MPC, which in turn generates control signals for the inverter. The control states of the two MPCs are constrained with the maximum limits of the drive system. The state feedback is achieved with a standard Kalman filter, which estimates the nonmeasured load torque. For a fair comparison, both approaches are applied to the same IM at the same operational circumstances. The control approaches are implemented and validated in an experimental environment using the same sampling frequency on the same test bench (3.7 kW IM drive). The behavior of the control approaches is assessed by applying reference and disturbance steps to the system in different operational modes. Comparison of the predictive schemes leads to the conclusion that the both MPC approaches achieve similar performances. However, the CCS-MPC scheme has a smaller current ripple and is of low computational complexity. The computing duration is not very different for the three tested schemes. CCS-MPC can cope with a less powerful DSP than for FCS.
A fixed-time trajectory tracking control method for uncertain robotic manipulators with input saturation based on reinforcement learning (RL) is studied. The designed RL control algorithm is ...implemented by a radial basis function (RBF) neural network (NN), in which the actor NN is used to generate the control strategy and the critic NN is used to evaluate the execution cost. A new nonsingular fast terminal sliding mode technique is used to ensure the convergence of tracking error in fixed time, and the upper bound of convergence time is estimated. To solve the saturation problem of an actuator, a nonlinear antiwindup compensator is designed to compensate for the saturation effect of the joint torque actuator in real time. Finally, the stability of the closed-loop system based on the Lyapunov candidate is analyzed, and the timing convergence of the closed-loop system is proven. Simulation and experimental results show the effectiveness and superiority of the proposed control law.
This article investigates the predefined time trajectory tracking control of uncertain nonlinear robotic systems. A radial basis function neural network (RBFNN) is used to estimate uncertainties in ...the robotic system dynamics. To avoid the singularity of terminal sliding-mode control (TSMC), a modified sliding variable is adopted. In order to realize that the tracking errors can converge to a small neighborhood of the origin in predefined time , within which the maximum convergence time can be adjusted by explicit parameters in advance, a nonsingular TSMC based on the RBFNN is proposed. Experiments on a ROKAE platform demonstrate the effectiveness and advantage of the proposed control method.
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