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In this paper, a new combination of fractional order calculus and finite time sliding mode control, used to design an aircraft autopilot. This combination aims to reduce the chattering phenomena and have a smoother control signal than conventional sliding mode. Fractional order control uses fractional integrator and derivative to improved integer order control methods. The sliding surface and sliding mode control law is proposed to reduce the chattering phenomena and also, closed-loop stability is guaranteed too. Using this algorithm, a robust autopilot against aerodynamic coefficients uncertainty is designed for an aircraft and proposed control law is utilized to stabilize the close loop system by Lyapunov stability theorem. The proposed autopilot is applied to the aircraft model and simulation results illustrate the reduction of chattering phenomena.

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In this paper, a low power and wideband Regulated Cascode (RGC)-based Transimpedance Amplifier (TIA) is presented to be used for the short range optical receiver systems. In this structure, input dominant parasitic capacitance is isolated by adding a cascoded inverter amplifier as a fully active feedback network in the booster of an RGC amplifier. As a result, a 6.4 GHz bandwidth is obtained at a lower power consumption. In addition, for eliminating the effect of output parasitic capacitance by resonating with an inductor and widening the bandwidth, an active inductive load is implemented at the output node of the proposed TIA circuit. Therefore, considering two main points of isolation of input parasitic capacitance effect and reduction of load parasitic capacitance effect, bandwidth is increased without using a high amount of power consumption. Based on the results simulated in HSPICE using 90 nm CMOS technology, the proposed TIA can reach the data bit rate of 10Gb/s. In addition, the proposed TIA consumes only 1.6mW of power, and has the gain of 40dBΩ across the 6.4 GHz of bandwidth.

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The paper presents an optimal and coordinated power oscillation damper based on a wind turbine and power system stabilizer (PSS) to maintain the power system stability and damp inter-area oscillations. The optimal and coordinated design of the PSS located at the generator site and the damper which was installed in the control section of the doubly-fed induction generator (DFIG) is defined as an optimization problem and simulations have been performed in MATLAB software environment. To determine optimal coefficients of the PSS and damper, the metaheuristic salp swarm optimization (SSA) algorithm was employed with an objective function that aimed to minimize the error caused by frequency deviations of two areas. Due to the use of wide-area measurement systems (WAMS) in the proposed damper to enhance controllability and observability of most of the oscillation modes, time delays resultant from the WAMS was also taken into account. Additionally, uncertainties of wind intermittency and time delay of WAMS were calculated probabilistically. The suggested method was applied to a six-machine two-area power system with a wind farm. The obtained simulation results highlighted and validated the superior performance and stability of the power system as a result of using the proposed method.

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Abstract: This paper designs an optimal controller for the simultaneous determination of physical model parameters and LQR controller parameters. In some systems, it is possible to determine some of the model parameters by the designer. In conventional methods of optimal controller design for this group of systems, first, the model parameters are determined by the designer, and then in a separate step, the controller is designed for the definite model. In this paper, a method for the simultaneous determination of these two sets of parameters is presented for continuous-time linear systems. Simultaneous parameter determination is a nonlinear and non-convex optimization problem that in this paper a new method is considered to solve this problem. The non-convex optimization problem is transformed into a convex optimization problem by performing simplifications and then solved by the CVX toolbox of MATLAB software. The result is a controller with less control cost in comparison to conventional methods for this group of systems. By providing a simulation example, the performance improvement of the proposed method is shown.