An improved adaptive iterative learning algorithm is applied on manipulators with repetitive time-varying disturbance. The saturation function was used when designed control law to reduce the torque chattering problem, and to force the manipulators to track time-varying reference signal fast, correctly and with assigned speed. The effectiveness of the proposed control system is demonstrated by Lyapunov analysis and simulation results: when the number of iteration increase, the tracking error will converge to zero uniformly with respect to the finite time interval, and chattering phenomenon reduced.

Adaptive Iterative Learning Control for Robot Manipulators

This article considers the neural adaptive control issues of a category of non-integer-order non-square plants with actuator Nonlinearities and Asymmetric Time-Varying pseudo-State Constraints. First, the original non-square non-affine system with input nonlinearities is transformed into an equivalent affine-in-control square model by defining a set of auxiliary variables and by employing the mean-value theorem. Second, Neural networks and Nussbaum functions are exploited to obviate the requirement of a complete knowledge of the system dynamics and the control directions, respectively. Third, a novel adaptive dynamic surface control method based on Caputo fractional derivative definitions and fractional order filters is developed to overcome the “explosion of complexity” problem in the traditional backstepping design process and to determine the parameter update laws and control signals, concurrently. Then, Asymmetric Barrier Lyapunov Functions with error variables are adopted to ensure the uniform stability of the closed-loop system and to prevent the violation of the full pseudo-State constraints. The novelties and contributions of this article are: (1) through the introduction of new technical Lemmas and corollaries, existing control design and stability theories linked to integer-order square systems are developed and extended to non-square non-integer-order ones. (2) all signals, including variables and errors in the closed-loop system are semi-global practical finite-time stability whereas the the tracking errors are asymptotically driven to zero without transgression of the constraints. Finally, the effectiveness and potential of the proposed control approach are substantiated by two example simulations.

Neural network controller design for fractional-order systems with input nonlinearities and asymmetric time-varying Pseudo-state constraints

Field programmable systems-on-chip (FPS-oCs) are heterogeneous reconfigurable platforms consisting of hard processors and FPGA fabric. They provide software designers with an efficient way to accelerate the execution of their algorithms and hardware designers with much more high-level processing power than that provided by soft-cores implemented in standard logic FPGA resources. Despite these very useful characteristics, the penetration of FPSoCs in digital designs for industrial electronics applications is very limited. There is a general agreement among researchers in the area that one of the main reasons for this is the lack of knowledge about the best way to interconnect the processors and the FPGA fabric in these devices. To address this issue, this paper presents an extensive characterization and analysis of processor-FPGA communications in a widely used family of FPSoCs, namely Cyclone V devices. To the best of authors´ knowledge, this is the most complete study of FPSoCs devices in this regard to date. From the experiments conducted and the results obtained, a set of design guidelines are introduced to help FPSoC designers take the most possible advantage of the excellent characteristics of these devices.

Performance Characterization and Design Guidelines for Efficient Processor–FPGA Communication in Cyclone V FPSoCs

Wheeled mobile robots present a typical case of complex systems with nonholonomic constraints. In the past few years, the dominance of these systems has been a very active research field. In this paper, a new method based on an integral sliding mode control for the trajectory tracking of wheeled mobile robots is proposed. The controller is designed to solve the reaching phase problem with the elimination of matched disturbances and minimize the unmatched one. We distinguish two parts in the suggested controller: a high-level controller to stabilize the nominal system and a discontinuous controller to assess the trajectory tracking in the presence of disturbances. This controller is robust during the entire motion. The effectiveness of the proposed controller is demonstrated through simulation studies for the unicycle with matched and unmatched disturbances.

/pdf/integral-sliding-mode-control-for-trajectory-tracking-of-d81sbv5c20.pdf

Integral Sliding Mode Control for Trajectory Tracking of Wheeled Mobile Robot in Presence of Uncertainties

Advanced Robotics

HIL simulation approach for a multicellular converter controlled by sliding mode

Switched mode DC-DC converters are electronic circuits which convert a voltage from one level to a higher or lower one. They are considered to be the most advantageous supply tools for feeding some electronic systems in comparison with linear power supplies which are simple and have a low cost. However, they are inefficient as they convert the dropped voltage into heat dissipation. The switched-mode DC-DC converters are more and more used in some electronic devices such as DC-drive systems, electric traction, electric vehicles, machine tools, distributed power supply systems and embedded systems to extend battery life by minimizing power consumption (Rashid, 2001). There are several topologies of DC-DC converters which can be classified into non-isolated and isolated topologies. The principle non-isolated structures of the DC-DC converters are the Buck, the Buck Boost, the Boost and the Cuk converters. The isolated topologies are used in applications where isolation is necessary between the input and the load. The isolation is insured by the use of an isolating transformer. The DC-DC converters are designed to work in open-loop mode. However, these kinds of converters are nonlinear. This nonlinearity is due to the switch and the converter component characteristics. For some applications, the DC-DC converters must provide a regulated output voltage with low ripple rate. In addition, the converter must be robust against load or input voltage variations and converter parametric uncertainties. Thus, for such case the regulation of the output voltage must be performed in a closed loop control mode. Proportional Integral and hysteretic control are the most used closed loop control solutions of DC-DC converters. This can be explained by the fact that these control techniques are not complicated and can be easily implemented on electronic circuit devises. Nowadays, the control systems such as microcontrollers and programmable logic devises are sophisticated and allow the implementation of complex and time consuming control techniques. The control theory provides several control solutions which can be classified into conventional and non-conventional controls. Many conventional controls, such as the PID control, were applied to DC-DC converters. The design of the linear controller is based on the linearized converter model around an equilibrium point near which the controller gives

/pdf/sliding-mode-control-and-fuzzy-sliding-mode-control-for-dc-fnc2en7cxq.pdf

Sliding Mode Control and Fuzzy Sliding Mode Control for DC-DC Converters

This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.

/pdf/adaptive-internal-model-control-of-a-dc-motor-drive-system-t9n4z0ddrp.pdf

Adaptive Internal Model Control of a DC Motor Drive System Using Dynamic Neural Network

This paper proposes a Fuzzy Sliding Mode Control (FSMC) as a control strategy for Buck-Boost DC-DC converter. The proposed fuzzy controller specifies changes in the control signal based on the knowledge of the surface and the surface change to satisfy the sliding mode stability and attraction conditions. The per- formances of the proposed fuzzy sliding controller are compared to those obtained by a classical sliding mode controller. The satisfactory simulation results show the efficiency of the proposed control law which reduces the chattering phenomenon. Moreover, the obtained results prove the robustness of the proposed control law against variation of the load resistance and the input voltage of the studied converter.

Chattering phenomenon supression of buck boost DC-DC converter with Fuzzy Sliding Modes Control

This paper deals with the design and the control of multiphase interleaved bidirectional DC-DC converter This converter is used for Electric Vehicle (EV) applications to convert and increase energy storage system voltage from low side voltage to high side voltage, which is necessary to feed the inverter used to drive the traction motor The proposed converter can be also used to connect the energy storage system to the smart grid To increase the performance of high side voltage and to have equal sharing of the load current in each converter module a fuzzy sliding mode control is proposedÂ  The control method is tested by simulation of 4 interleaved bidirectional DC-DC converter associated with the three-phase inverter coupled with a 3 phase induction motor The simulation results exposed the robustness of the proposed control method under some disturbancesÂ Â

https://www.ijsmartgrid.org/index.php/ijsmartgridnew/article/download/102/pdf

Multiphase Interleaved Bidirectional DC-DC Converter for Electric Vehicles and Smart Grid Applications

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