UNFALSIFIED ADAPTIVE CONTROL is a new approach in supervisory CONTROL that ensures the selection of a stabilizing CONTROLler from a CONTROL set based on the system input-output data. A prerequisite for ensuring stability is the existence of a pre-designed CONTROLler set that contains a stabilizing CONTROLler. The supervisor selects the CONTROLler based on the cost function calculated with the system input-output data. In this method, the CONTROL system performance is restricted to the CONTROLlers of the CONTROL set. In this paper, the CONTROLler set update is performed by introducing the concept of performance falsification along with the stability falsification of the active CONTROLler. To falsify the performance of the CONTROLler set, the structure of the model reference is proposed to evaluate the performance of the CONTROL system. In case of performance falsification, a new CONTROLler is designed and added to the CONTROLler set based on system data and without using any model. To design the CONTROLler, a linear matrix inequality problem is solved. In this paper, no system model is used, and the presented method is completely model-free and data-oriented. The simulation results show the performance improvement of the proposed method compared to other methods in a standard robust ADAPTIVE benchmark system.

Feedback CONTROL loops are hidden but ubiquitous mechanisms all around the modern world. The current CONTROL technology utilizes model-based advanced CONTROL systems design. The philosophical background thought behind such designs is an inductivism-based reductionist-mechanistic approach. Despite its outstanding problem-solving achievements, it is argued that a deduction-based philosophical approach in the form of data-driven CONTROL system design has emerged. UNFALSIFIED CONTROL is a notable outcome of philosophical thinking and is briefly reviewed.

One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust ADAPTIVE CONTROL method based on dynamic programming has been used to design a stabilizing power system and a complementary static var compensator (SVC) CONTROLler. By applying a single line to ground fault in the network, the robustness of the designed CONTROL systems is demonstrated. Also, the simulation results of the method used in this paper are compared with CONTROLlers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust ADAPTIVE CONTROL method based on dynamic programming for the stabilizing design of the power system and the complementary SVC CONTROLler. The performance of the CONTROL method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

UNFALSIFIED ADAPTIVE CONTROL (UAC) is a recently proposed robust ADAPTIVE CONTROL strategy. In this paper, the UAC principles and algorithms are reviewed and Multi-Model UAC is followed as an intermediate between UAC and multiple model CONTROL. Different approaches in UAC and MMUAC are studied. Also, Multi-Model UNFALSIFIED Generalized Predictive CONTROL (MMUGPC) is proposed, which is a new CONTROL design strategy in the UAC framework. For an uncertain system, by utilizing several generalized predictive CONTROLlers and discrete switching between them with UNFALSIFIED CONTROL, a new structure is proposed and appropriate equations are derived. Simulation results show the effectiveness of proposed Multi-Model UNFALSIFIED Generalized Predictive CONTROL.

UNFALSIFIED ADAPTIVE CONTROL strategy is a data-driven approach in robust ADAPTIVE CONTROL that selects the stabilizing CONTROLler from an the available CONTROL bank based on the input-output system’s data. Selection is done without activating the CONTROLlers by using the virtual reference signal and a cost function. Stability of the closed loop system is guaranteed. In this paper, inspired by the UNFALSIFIED CONTROL approach, the goal is to select a CONTROLler from the available pre-designed CONTROLler bank that has the highest level of disturbance attenuation. The selection is based on the system’s data by using a cost function without disturbance measurement. By introducing a new concept called virtual disturbance, the performance of CONTROLlers is evaluated without activation. The convergence of the algorithm and the disturbance attenuation level of the proposed method have been proven in a theorem. Simulation results show performance of the proposed method on a wind turbine for various wind speed disturbances.

This article investigates the problem of simultaneous attitude and vibration CONTROL of a flexible spacecraft to perform high precision attitude maneuvers and reduce vibrations caused by the flexible panel excitations in the presence of external disturbances, system uncertainties, and actuator faults. ADAPTIVE integral sliding mode CONTROL is used in conjunction with an attitude actuator fault iterative learning observer (based on sliding mode) to develop an active fault tolerant algorithm considering rigid-flexible body dynamic interactions. The discontinuous structure of fault-tolerant CONTROL led to discontinuous commands in the CONTROL signal, resulting in chattering. This issue was resolved by introducing an ADAPTIVE rule for the sliding surface. Furthermore, the utilization of the sign function in the iterative learning observer for estimating actuator faults has not only enhanced its robustness to external disturbances through a straightforward design, but has also led to a decrease in computing workload. The strain rate feedback CONTROL algorithm has been employed with the use of piezoelectric sensor/actuator patches to minimize residual vibrations caused by rigid-flexible body dynamic interactions and the effect of attitude actuator faults. Lyapunov's law ensures finite-time overall system stability even with fully coupled rigid-flexible nonlinear dynamics. Numerical simulations demonstrate the performance and advantages of the proposed system compared to other conventional approaches.

Distance-based clustering methods categorize samples by optimizing a global criterion, finding ellipsoid clusters with roughly equal sizes. In contrast, density-based clustering techniques form clusters with arbitrary shapes and sizes by optimizing a local criterion. Most of these methods have several hyper-parameters, and their performance is highly dependent on the hyper-parameter setup. Recently, a Gaussian Density Distance (GDD) approach was proposed to optimize local criteria in terms of distance and density properties of samples. GDD can find clusters with different shapes and sizes without any free parameters. However, it may fail to discover the appropriate clusters due to the interfering of clustered samples in estimating the density and distance properties of remaining unclustered samples. Here, we introduce ADAPTIVE GDD (AGDD), which eliminates the inappropriate effect of clustered samples by ADAPTIVEly updating the parameters during clustering. It is stable and can identify clusters with various shapes, sizes, and densities without adding extra parameters. The distance metrics calculating the dissimilarity between samples can affect the clustering performance. The effect of different distance measurements is also analyzed on the method. The experimental results conducted on several well-known datasets show the effectiveness of the proposed AGDD method compared to the other well-known clustering methods.

A major characteristic of polymerization reactors is their complex nonlinear behaviour. Due to this nonlinear nature, CONTROL of polymerization reactors has always been a challenging task. In this article the performances of three ADAPTIVE CONTROL schemes, namely, self-tuning CONTROL(STC), ADAPTIVE internal model CONTROL (AIMC) and ADAPTIVE robust generic model CONTROL (ARGMC) are compared through simulation studies. The temperature CONTROL of polymerization of methyl methacrylate (MMA), which is highly exothermic, is chosen for simulation. Simulation results show that all three schemes can CONTROL the process but the best performance belongs to STC scheme.

This paper discusses the flight CONTROL strategy based on ADAPTIVE Dynamic Inversion (ADI) with two-time-scale separation for airplane. Because of nonlinear behavior of flight dynamics, the flight CONTROL problem is a rather important and complex issue. In addition to traditional methods, e.g., classic CONTROLler, Dynamic inversion methods, fuzzy and neural networks have been used. After reviewing these methods, Combination ADAPTIVE dynamic inversion Method is designed. In this structure, the CONTROL system attempts to track the angle of attack, the sideslip angle and the roll angle in wind frame (m, a, b). Six degree-of-freedom nonlinear equations of motion are considered for tracking the input commands. Dynamic inversion technique needs an exact and accurate flight dynamics, and to avoid this problem, we use an ADAPTIVE CONTROLler. Two-timescale based system dynamics are divided into slow outer variables and fast inner variables. ADAPTIVE CONTROLler and Dynamic inversion algorithm are used in inner and outer loops, respectively. The performance of the proposed method compares with Full Dynamic Inversion (DI) method. Simulation results demonstrated the efficacy of ADAPTIVE Dynamic Inversion CONTROLler.

Exoskeleton robot has attracted attention of many researchers because it realizes an old aspiration to attain a machine which is worn by man and maximizes his might via its powerful actuators. Thorough coordination between robot movements and that of user constitutes the greatest complexity of exoskeleton technology. Investigations showed that impedance CONTROL (IC) is suitable for this application but the present forms of IC are mostly dedicated to industrial robots which have significant differences with exoskeleton. In this article a versatile form of IC for the mentioned application is developed. Besides, according to perpetual uncertainties in load and measured force signals, for the first time an ADAPTIVE method for IC of exoskeleton robot is implemented. Simulating operation of robot in tracking user's walking motion while carrying a load of 50 (Kg) and with uncertainties in load and measured forces, proves efficiency of the proposed CONTROL method. Tracking error during simulation is almost zero and torques needed at interfaces are immaterial.